Data processing – Eagle Rock IS http://eaglerock-is.com/ Tue, 08 Nov 2022 15:19:30 +0000 en-US hourly 1 https://wordpress.org/?v=5.9.3 https://eaglerock-is.com/wp-content/uploads/2021/10/icon-56-120x120.png Data processing – Eagle Rock IS http://eaglerock-is.com/ 32 32 Why creating smart cities requires real-time data processing https://eaglerock-is.com/why-creating-smart-cities-requires-real-time-data-processing/ Tue, 08 Nov 2022 15:19:30 +0000 https://eaglerock-is.com/why-creating-smart-cities-requires-real-time-data-processing/ To manage the growing urbanization of smart cities, urban planners and managers must turn to real-time data processing By 2030, 28% of the world’s population is expected to live in a city of at least one million people, according to an urbanization report from the Government Office for Science. In England alone, 82.9% of the […]]]>

To manage the growing urbanization of smart cities, urban planners and managers must turn to real-time data processing

By 2030, 28% of the world’s population is expected to live in a city of at least one million people, according to an urbanization report from the Government Office for Science. In England alone, 82.9% of the population lived in an urban area in 2019, and this continues to rise. To manage these levels of urbanization, city planners and managers are turning to modern technologies and cutting-edge networks.taking advantage of the The Internet of Things (IoT) to support “smart city” solutions.

Data, and the ability to process it quickly and transparently, is critical to the connected and intelligent networks that make today’s cities live and the transport systems that connect the cities of a country. IoT usage has grown over the past few years and figures from Statista suggest that there will be over 29 billion IoT devices in the world by 2030.

Think smart homes, street safety, water monitoring, healthcare, traffic lighting, traffic control, and smart waste management

The reason for this rapid growth is the large number of applications for which IoT serves a purpose. Think smart homes, street safety, water monitoring, healthcare, traffic lighting, traffic control, and smart waste management.

The role of the database and data platforms

However, these applications will not work properly unless IoT-based strategies to develop smart cities are database-driven. Modern databases can automate the dissemination of information from large numbers of rapidly changing data points and work in tandem with real-time data platforms capable of analyzing large volumes of data at city ​​scale collected through IoT systems. All data is ingested and processed in real time, from gigabyte to petabyte, and delivered to ensure vital decisions can be made on the spot.

What does real time mean in this scenario?

Data is processed in less than a millisecond, and what’s more, it’s processed error-free. This enables city services to be optimized through intelligent data flow, and it is already having an impact in the following areas:

Smart energy:

IoT sensors are essential for adopting smart electricity meters, improved energy distribution, energy networks that can self-heal, networks in buildings and factories, leak detection and waste collection just in time.

© Patrick Daxenbichler

Environmental controls and sustainability:

IoT sensors can help maximize energy efficiency, monitor pollution levels, traffic control and sustainable resources. Specifically, they can provide data on how to reduce emissions and eliminate waste.

Facilities Management:

Smart buildings rely on IoT-based sensors to improve energy efficiency, for example by automating lighting controls and improving space utilization to reduce costs.

Mobility and connected transport:

Surveillance of public transport can improve safety and hygiene. At a time, traffic controlparking and many other transit-related services increasingly rely on real-time information to maintain traffic, utilize parking spaces, and provide predictive information for road management.

The primary objective of a smart city is to provide citizens with better living conditions

Public Safety and Security:

The primary objective of a smart city is to provide citizens with better living conditions. Cameras and real-time video surveillance help reduce crime through motion detection and real-time crowdsourcing of crime data, including identifying security vulnerabilities, active crime tracking and monitoring. speeding up the authorities’ response times.

The impact of 5G

5G offers faster, more reliable and more secure connectivity. The development of everything from self-driving cars to smart grids for renewable energy to AI-based robots in factories is enabled by 5G. And the speed and latency it delivers means networks can even support billions of IoT-connected devices.

But with this progress comes much more data

But with that progress comes much more data — up to 181 zettabytes by 2025, according to Statista. This is more than six times the amount processed in 2018.

What 5G will bring to cities are faster connections and greater reliability; we will benefit from more capacity at lower cost, and the higher bandwidth and lower latency that smart city applications such as real-time connected vehicles and traffic data and infrastructure security rely on will be offered by the 5G.

We can also expect rapid developments in key technology areas, including artificial intelligence (AI) and machine learning (ML), video surveillance and, of course, greater support for IoT and self-driving cars.

This will catalyze smart city progress, but the success of 5G will depend on data processing and analysis powered by modern real-time data platforms.

These platforms can move large amounts of data across the network and create an affordable way to store data so it can be easily accessed and analyzed.

Create livable cities

The smart cities we build must also be resource efficient. To do this, we need instant and accurate data analytics that can decipher the huge volumes of data from multiple sources, including geospatial data, traffic data, pedestrian traffic data, and even crime statistics. .

Of course, data also comes from social media channels, audio, video and smart devices, coinciding with a growth in unstructured data. This means that organizations developing smart cities must understand and be prepared to use the right tools to dig deep into all the complex data in real time. The more they can share, the more likely a smart city will succeed.

At present, the motivation for creating a smart city is that it can reap economic, environmental and social benefits. The use of real-time data management and processing capabilities supports a new ecosystem of municipal services. It enables data-driven governments and knowledge-driven policies that can improve operational efficiency.

Written by Martin James, Vice President EMEA at Aerospike

from the editor Recommended Articles

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What is the stock price of Automatic Data Processing, Inc. (NASDAQ:ADP) doing? https://eaglerock-is.com/what-is-the-stock-price-of-automatic-data-processing-inc-nasdaqadp-doing/ Sun, 30 Oct 2022 14:00:12 +0000 https://eaglerock-is.com/what-is-the-stock-price-of-automatic-data-processing-inc-nasdaqadp-doing/ Let’s talk about the popular Automatic Data Processing, Inc. (NASDAQ: ADP). The company’s shares have seen decent share price growth at the teen level on the NASDAQGS over the past few months. With many analysts covering large-cap stocks, we can expect any price-sensitive announcements to have already factored into the stock price. But what if […]]]>

Let’s talk about the popular Automatic Data Processing, Inc. (NASDAQ: ADP). The company’s shares have seen decent share price growth at the teen level on the NASDAQGS over the past few months. With many analysts covering large-cap stocks, we can expect any price-sensitive announcements to have already factored into the stock price. But what if there is still an opportunity to buy? Let’s take a closer look at the Automatic Data Processing valuation and outlook to see if there is still a bargain opportunity.

See our latest analysis for automatic data processing

Is automatic data processing always cheap?

The stock currently seems quite valued according to my valuation model. It trades around 6.6% below my intrinsic value, which means that if you buy automatic data processing today, you will pay the right price for it. And if you think the true value of the business is $259.77, then there’s not much benefit to be gained from poor pricing. On top of that, ADP has a low beta, which suggests its stock price is less volatile than the broader market.

What does the future of automatic data processing look like?

earnings-and-revenue-growth

Future prospects are an important aspect when considering buying a stock, especially if you are an investor looking to grow your portfolio. Buying a big company with solid prospects at a cheap price is always a good investment, so let’s also take a look at the company’s future expectations. With profits expected to increase by 36% over the next two years, the future looks bright for automatic data processing. It seems that a higher cash flow is expected for the stock, which should translate into a higher valuation of the stock.

What this means for you

Are you a shareholder? It looks like the market has already priced in the positive outlook for ADP, with the stock trading around its fair value. However, there are also other important factors that we have not considered today, such as the financial strength of the company. Have these factors changed since the last time you looked at the stock? Will you be confident enough to invest in the business if the price drops below its fair value?

Are you a potential investor? If you’ve been keeping an eye on ADP, now might not be the best time to buy, given that it’s trading around its fair value. However, the positive outlook is encouraging for the company, which means it is worth digging deeper into other factors such as the strength of its balance sheet, in order to take advantage of the next price drop.

If you want to learn more about automatic data processing as a business, it is important to be aware of the risks it faces. Example: we have identified 1 warning sign for automatic data processing you should be aware.

If you are no longer interested in automatic data processing, you can use our free platform to see our list of more 50 other stocks with strong growth potential.

Feedback on this article? Concerned about content? Get in touch with us directly. You can also email the editorial team (at) Simplywallst.com.

This Simply Wall St article is general in nature. We provide commentary based on historical data and analyst forecasts only using unbiased methodology and our articles are not intended to be financial advice. It is not a recommendation to buy or sell stocks and does not take into account your objectives or financial situation. Our goal is to bring you targeted long-term analysis based on fundamental data. Note that our analysis may not take into account the latest announcements from price-sensitive companies or qualitative materials. Simply Wall St has no position in the stocks mentioned.

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Automatic Data Processing (NASDAQ:ADP) Releases Fiscal 2023 Earnings Forecast https://eaglerock-is.com/automatic-data-processing-nasdaqadp-releases-fiscal-2023-earnings-forecast/ Thu, 27 Oct 2022 17:33:59 +0000 https://eaglerock-is.com/automatic-data-processing-nasdaqadp-releases-fiscal-2023-earnings-forecast/ Automatic Data Processing (NASDAQ: ADP), which previously provided earnings forecasts for fiscal year 2023, released an updated version on Wednesday. The company’s expected quarterly earnings per share will be $8.06 to $8.20, which is above the consensus estimate of $8.03 for those earnings. Additionally, the company provided a revenue forecast of between $17.82 billion and […]]]>

Automatic Data Processing (NASDAQ: ADP), which previously provided earnings forecasts for fiscal year 2023, released an updated version on Wednesday. The company’s expected quarterly earnings per share will be $8.06 to $8.20, which is above the consensus estimate of $8.03 for those earnings. Additionally, the company provided a revenue forecast of between $17.82 billion and $17.98 billion, which is significantly lower than the average revenue estimate of $17.87 billion.

Automatic Data Processing (NASDAQ: ADP), in a report made publicly available on July 27, provided details on the company’s performance. The business services provider reported earnings per share for the quarter of $1.50, $0.02 higher than the consensus earnings-per-share forecast made by industry experts, who had predicted earnings per share. of $1.48 for the quarter. The return on equity for automatic data processing was calculated at 66.25%, while the company’s net margin was calculated at 17.87%. Contrary to the $4.05 billion in sales that relevant industry professionals predicted the company would achieve in the quarter, the company generated $4.13 billion in revenue during this period. The company posted earnings of $1.20 per share in the same period last year compared to the current year. In the third fiscal quarter of automatic data processing, the company recorded a year-over-year revenue increase of 10.5% over the prior year. Analysts who study the stocks believe the automatic data processing will return $8.05 per share in the current fiscal year.
The NASDAQ ADP hit a new session high of $240.04 during Wednesday trading, reflecting a rise of $2.28 from the previous day’s closing price. Compared to the typical volume of 1,818,754 shares, there were only 69,705 trades involving the company’s stock. The debt ratio, quick ratio, and current ratio all equal 0.93, and all three have a value of 0.99. The moving average of the company’s stock price over the past 200 days is $227.56 and the moving average for the past fifty days is $238.20. The company has a price/earnings ratio of 33.87, a price/earnings/growth ratio of 2.41 and a beta value of 0.83. These three ratios measure the cost of the business relative to its future earnings potential. Its current market value is $99.69 billion. The 52-week low and the 52-week high for automatic data processing are currently at the same price level of $261.59. The stock is currently trading at $192.26.
Recently, the company has been in communication with a variety of analysts, and they have provided their comments. In a September 20 research note, Cowen announced that it was raising its price target on automatic data processing from $230.00 to $236.00. In a research report published on July 20, Wolfe Research lowered its price target on Automatic Data Processing shares from $235.00 to $210.00. On October 12, StockNews.com released a research report announcing that it would begin covering automatic data processing stocks. The report was released on Wednesday. They suggested that shareholders continue to keep their shares in the company. Following the release of their analysis on Tuesday, September 20, Cowen raised their price target for Automatic Data Processing from $230.00 to $236.00. The new price target can be found here. Barclays raised its price target for automatic data processing to $280.00 in a research report released on Tuesday, August 9. As a result, the company now has four price targets to hit. Nine equity research experts gave the stock a “hold” rating, while two said they thought it was a good investment and should be held. bought. According to information from Bloomberg, the stock is given an overall rating of “Hold” by the market, and an average price target of $236.85 is expected.

Additionally, the company announced that it will pay a quarterly dividend, distributed on the first Saturday in October this year. On Friday, September 9, dividends of $1.04 were distributed to owners who still held their shares. This took place after the distribution date of the previous Friday, September 2. As of September 8, it was considered that this dividend had been paid in full. This translates into a yield of 1.73% and a dividend payment of $4.16 per year for each shareholder. At this point, the distribution rate for automatic data processing is 59.34%.

Christopher D’Ambrosio, who serves as the company’s vice president, sold 174 shares of the company on September 8. This was yet another new turn of events. A total of $41,184.06 worth of shares was sold at an average price of $236.69 per share resulting in a total of $41,184.06 worth of shares. After the completion of the sale, the vice president now has direct control over 3,157 shares of the company. These shares are worth approximately $747,230.33 each. The United States Securities and Exchange Commission has received legal documents on the transaction, which can be viewed here. Christopher D’ambrosio, vice president of automatic data processing, reportedly sold 174 shares of the company on September 8, as reported in previous news about automatic data processing. The shares were sold on the open market for a total price of $236.69 per share, equivalent to the price of $21,184.06 for all the shares. After the transaction was completed, the vice president was able to buy 3,157 shares of the company. The total value of these shares is $747,230.33, so buying the VP was a good investment. If you follow the link, which will take you to a legal filing filed with the SEC, you will have the opportunity to acquire additional information regarding the transaction.
Additionally, on August 8, Vice President Donald Weinstein sold 10,150 shares of the company. The transaction was valued at $2,537,500.00 as each share was purchased at an average price of $250.00. As a direct result of the transaction, the company’s vice president now owns 41,035 shares of the company, worth $10,258,750. Disclosures related to the sale can be found in this section of the website. Company insiders sold a total of 107,034 shares in the previous ninety days, generating total revenue of $25,514,241. The current ownership of the Company’s shares by insiders is 33.3%.

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Global Data Processing Unit Market to Hit $5.5 Billion by https://eaglerock-is.com/global-data-processing-unit-market-to-hit-5-5-billion-by/ Fri, 21 Oct 2022 15:00:00 +0000 https://eaglerock-is.com/global-data-processing-unit-market-to-hit-5-5-billion-by/ Portland, OR, Oct. 21, 2022 (GLOBE NEWSWIRE) — According to the report released by Allied Market Research, the global data processing unit market generated $553.96 million in 2021 and is expected to reach $5.5 billion by 2031, growing at a CAGR of 26.9% from 2022 to 2031. changing market trends, market size and estimates, value […]]]>

Portland, OR, Oct. 21, 2022 (GLOBE NEWSWIRE) — According to the report released by Allied Market Research, the global data processing unit market generated $553.96 million in 2021 and is expected to reach $5.5 billion by 2031, growing at a CAGR of 26.9% from 2022 to 2031. changing market trends, market size and estimates, value chain, key investment pockets, drivers and opportunities, competitive landscape and regional landscape. The report is a useful source of information for new entrants, shareholders, early adopters and stockholders in introducing necessary strategies for the future and taking essential actions to significantly strengthen and increase their position in the market.

Download a FREE sample report (231 page PDF with information, graphs, tables, figures) at https://www.alliedmarketresearch.com/request-sample/13234

Report coverage and details:

Report cover Details
Forecast period 2022–2031
Year of reference 2021
Market size in 2021 $553.96 million
Market size in 2031 $5.5 billion
CAGR 26.9%
Number of pages in the report 231
Segments Covered Type, data center type, application and region
Drivers Increase in internet penetration
Increased penetration of high-end cloud computing in enterprises
Opportunities Increasing Multicloud Adoption
Growth in popularity of 5G network capabilities
holds back increase in data privacy concerns
growing demand for managed services

COVID-19 scenario:

  • The COVID-19 outbreak has negatively impacted the growth of the global data processing unit market, owing to the occurrence of lockdowns in various countries across the globe.
  • With the governments of several countries imposing and extending lockdowns, production and manufacturing facilities across the world have been shut down, due to the crisis and unavailability of manpower.
  • These restrictions were imposed by the government to curb the spread of the virus during the pandemic. Considering the contributions of various industry experts belonging to the different stages of the value chain, such as OEMs, suppliers, integrators, end users and distributors, and the financial publication of various companies in the Data Processing Unit ecosystem Market is calculated to witness decline in 2019-2020.
  • However, the market is expected to recover from 2021 and remain in the growth phase during the forecast period.

The report offers detailed segmentation of the global data processing units market on the basis of type, data center type, application, and region. The report provides a comprehensive analysis of each segment and their respective sub-segment using graphical and tabular representation. This analysis can essentially help market players, investors and new entrants to determine and design strategies based on the fastest growing and highest revenue generating segments mentioned in the report.

Based on type, the FPGA-based segment held the largest market share in 2021, holding more than half of the global data processing unit market share, and is expected to maintain its leading status during the forecast period. The SOC-based segment, on the other hand, is expected to quote the fastest CAGR of 29.72% during the forecast period.

Based on data center type, the hyperscale segment held the largest market share in 2021, holding more than two-fifths of the global data processing unit market share, and is expected to maintain its dominant status over the course of the forecast period. The peripheral segment, on the other hand, is expected to quote the fastest CAGR of 33.51% during the forecast period.

Based on applications, the IT and telecommunications segment held the dominant market share in 2021, holding nearly two-fifths of the global data processing units market share, and is expected to maintain its leading status during the period. forecast. Also, the same segment is expected to quote the fastest CAGR of 29.91% during the forecast period. The report also includes other segments such as BFSI, Government, Energy & Utilities and Others.

Based on region, the North American market held the dominant market share in 2021, holding nearly two-fifths of the global data processing unit market share. The Asia-Pacific region, on the other hand, is expected to maintain its leading status during the forecast period. Also, the same region is expected to quote the fastest CAGR of 32.46% during the forecast period.

Do you want to acquire the data with a strategy and actionable insights? Find out before you buy – https://www.alliedmarketresearch.com/purchase-enquiry/13234

The report analyzes the main players of the global data processing units market such as NVIDIA Corporation (Mellanox Technologies), Marvell Technology Inc., Fungible, Inc., Broadcom Inc., Intel Corporation, Kalray, Resnics / Yisixin Technology (Shanghai) Co., Ltd., and Advanced Micro Devices, Inc. (Pensando Systems Inc.)

The report analyzes these key players of the global data processing units market. These market players have effectively used strategies such as joint ventures, collaborations, expansion, new product launches, partnerships, and others to maximize their foothold and prowess in the industry. The report is useful for analyzing recent developments, product portfolio, business performance, and operating segments of major market players.

Buy this research report http://surl.li/dkshx

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Allied Market Research (AMR) is a full-service market research and business consulting division of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global corporations as well as small and medium enterprises with unparalleled quality of “Market research reportsand “Business Intelligence Solutions”. AMR has a focused vision to provide business insights and advice to help its clients make strategic business decisions and achieve sustainable growth in their respective market area.

We maintain professional relationships with various companies which helps us to extract market data which helps us to generate accurate research data tables and confirm the utmost accuracy of our market predictions. Allied Market Research CEO Pawan Kumar helps inspire and encourage everyone associated with the company to maintain high quality data and help clients in every way possible to achieve success. All data presented in the reports we publish are drawn from primary interviews with senior managers of large companies in the relevant field. Our secondary data sourcing methodology includes extensive online and offline research and discussions with knowledgeable industry professionals and analysts.

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Near real-time seismic data processing helps scientists understand aftershocks https://eaglerock-is.com/near-real-time-seismic-data-processing-helps-scientists-understand-aftershocks/ Fri, 14 Oct 2022 18:51:47 +0000 https://eaglerock-is.com/near-real-time-seismic-data-processing-helps-scientists-understand-aftershocks/ A new method of automatically detecting and locating earthquakes uses artificial intelligence. The system has successfully located recent earthquakes in Taiwan and could help scientists monitor ongoing events. By Hao Kuo-Chen, Ph.D., Sun Wei-Fang, Chun-Ming Huangand Pan Sheng YanNational Taiwan University Quote: Kuo-Chen, H., Sun, W., Huang, C., Pan, S., 2022, Near real-time seismic data […]]]>

A new method of automatically detecting and locating earthquakes uses artificial intelligence. The system has successfully located recent earthquakes in Taiwan and could help scientists monitor ongoing events.

By Hao Kuo-Chen, Ph.D., Sun Wei-Fang, Chun-Ming Huangand Pan Sheng YanNational Taiwan University

Quote: Kuo-Chen, H., Sun, W., Huang, C., Pan, S., 2022, Near real-time seismic data processing helps scientists understand aftershocks, Temblor, http://doi.org /10.32858/temblor. 276

This article is also available in Traditional Chinese.

A magnitude 6.5 earthquake hit eastern Taiwan on Saturday, September 17. Just 17 hours later, a 6.9 magnitude main shock struck, rupturing the surface. The main shock damaged buildings, roads and bridges along the southern longitudinal valley, the boundary between the Eurasian and Philippine tectonic plates.
Many aftershocks followed. Although the larger Main Shock and Precursor Shock are important for understanding seismic hazards in the region, these smaller earthquakes, which are common after a large event, provide valuable information about the rupture process.

When an earthquake strikes, scientists analyze seismograms – plots of seismic waves recorded at stations scattered across the landscape. Accurately determining when primary (P) and secondary (S) seismic waves arrive at a station is critical to locating an earthquake. However, conventional methods for spotting the arrival of P and S waves in a sea of ​​seismic data are time-consuming, especially for aftershock sequences, when a considerable number of small earthquakes occur in a relatively short time. .

Being able to quickly assess aftershock distribution can help scientists track seismic hazard following large earthquakes and into the future, which is crucial for seismic risk management.

We recently developed artificial intelligence (AI) technology for wave detection, and since 2021 we have deployed five seismic stations in eastern Taiwan equipped with such capabilities. Fortunately, this network of stations was well placed to record the latest earthquake sequence that hit eastern Taiwan. We were able to successfully monitor the entire event, from seismicity to aftershocks, in near real time, as our artificial intelligence system, called SeisBlue, automatically detected the incoming waves. SeisBlue is a deep learning data processing platform for creating earthquake catalogs offline or in near real time.

Locations of SeisBlue stations and epicentres of precursor and main shocks. 1 credit

A catalog of earthquakes in near real time

In the 39 hours following the magnitude 6.5 shock, SeisBlue detected 6,104 earthquakes and located 1,223. Most of the aftershocks were triggered along a 20 kilometer (12 mile) stretch of the southern longitudinal valley. After a week, aftershocks extended 90 kilometers (55 miles). According to residents’ recollections, the damage to the construction was mainly caused by the main shock, which is consistent with our detection results.

SeisBlue located 1,223 earthquakes within 39 hours of the September 17 quake (Southern Black Star).  The Dark North Star is the main shock of magnitude 6.9.  1 credit
SeisBlue located 1,223 earthquakes within 39 hours of the September 17 quake (Southern Black Star). The Dark North Star is the main shock of magnitude 6.9. 1 credit

Within two days of the 6.5 magnitude shock, a catalog of earthquakes from the event, detected by SeisBlue, was presented to the public. Such a catalog of earthquakes assembled by conventional methods would have taken more than six months to create. The catalog will be used by seismologists and community planners for risk assessment and disaster relief and by the research community to identify potential locations of surface failures.

References

https://github.com/SeisBlue/SeisBlue

Mousavi, SM, Ellsworth, WL, Zhu, W., Chuang, LY, and Beroza, GC (2020). Seismic Transformer—an attentive deep learning model for simultaneous earthquake detection and phase selection. Natural Communications, 11(1), 1-12.

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Microsoft announces Syntex, a set of automated document and data processing services • TechCrunch https://eaglerock-is.com/microsoft-announces-syntex-a-set-of-automated-document-and-data-processing-services-techcrunch/ Wed, 12 Oct 2022 16:01:33 +0000 https://eaglerock-is.com/microsoft-announces-syntex-a-set-of-automated-document-and-data-processing-services-techcrunch/ Two years ago, Microsoft launched SharePoint Syntex, which leverages AI to automate the capture and classification of data from documents, building on existing SharePoint services. Today marks platform expansion in Microsoft Syntex, a set of new products and features, including file annotation and data extraction. Syntex reads, marks and indexes document content, whether digital or […]]]>

Two years ago, Microsoft launched SharePoint Syntex, which leverages AI to automate the capture and classification of data from documents, building on existing SharePoint services. Today marks platform expansion in Microsoft Syntex, a set of new products and features, including file annotation and data extraction. Syntex reads, marks and indexes document content, whether digital or physical, making it searchable and available in Microsoft 365 apps and helping manage the content lifecycle with security and retention settings.

According to Chris McNulty, director of Microsoft Syntex, the driving force behind the launch was the growing desire of customers to “do more with less”, especially in the face of a recession. A 2021 investigation from Dimensional Research found that more than two-thirds of companies leave valuable data untapped, primarily due to issues building pipelines to access that data.

“Just as business intelligence has transformed the way companies use data to make business decisions, Microsoft Syntex unlocks the value of the massive amount of content that resides within an organization,” McNulty said. to TechCrunch in an email interview. “Virtually any industry with large-scale content and processes will benefit from adopting Microsoft Syntex. In particular, we see the greatest alignment with industries that work with a higher volume of technically dense and regulated content – ​​financial services, manufacturing, healthcare, life sciences and retail among them.

Syntex offers tools for backup, archiving, analysis and document management as well as a viewer to add annotations and deletions to files. Containers allow developers to store content in a managed sandbox, while “scenario accelerators” provide workflows for use cases such as contract management, accounts payable, and more.

“The Syntex content processor allows you to create simple rules to trigger the next action, whether it’s a deal, an alert, a workflow, or just ranking your content in the right libraries and folders,” McNulty explained. “[Meanwhile,] the advanced viewer adds an annotation and inking layer on top of any visible content in Microsoft 365. Annotations can be done securely, with different permissions than the underlying content, and also without modifying the content underlying.

McNulty says clients like TaylorMade are exploring ways to use Syntex for contract management and assembly, standardizing contracts with common clauses around financial terms. The company also runs the service for processing orders, receipts and other transactional documents for accounts payable and finance teams, in addition to organize and secure emails, attachments and other documents for intellectual property and patent filings.

“One of the fastest growing content transactions is e-signature,” McNulty said. “[With Syntex, you] can submit e-signature requests using Syntex, Adobe Acrobat Sign, DocuSign, or one of our other partner e-signature solutions and your content remains in Microsoft 365 while it is reviewed and signed.

Syntex-like intelligent document processing is often touted as a solution to the problem of large-scale file management and orchestration. According from a single source, 15% of a company’s revenue is spent on creating, managing and distributing documents. Documents are not only expensive, they are time-consuming and error-prone. More than nine in 10 employees responding to an ABBY 2021 investigation said they were wasting up to eight hours a week sifting through documents to find data and using traditional methods creating a new document takes an average of three hours and results in six punctuation, spelling, omission or printing errors.

A number of startups are offering products to address this problem, including Hypatos, which applies deep learning to power a wide range of back-office automation with a focus on industries with heavy data processing needs. financial documents. Flatfile automatically learns how data imported from files should be structured and cleaned, while another vendor, Klarity, aims to replace humans for tasks that require large-scale document review, including purchase orders accounts, purchase orders and agreements.

As with many of its services announced today, Microsoft is obviously betting that scale will work in its favor.

“Syntex uses artificial intelligence and automation technologies from Microsoft, including synthesis, translation and optical character recognition,” McNulty said. “Many of these services are being made available to Microsoft 365 commercial accounts without an additional initial license under a new pay-as-you-go business model.”

Syntex begins rolling out today and will continue into early 2023. Microsoft says it will post additional details about service pricing and packaging on the Microsoft 365 message center and via licensing disclosure documentation in the coming months.

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Automatic Data Processing, Inc. (NASDAQ:ADP) VP Sells Stock for $57,544.20 https://eaglerock-is.com/automatic-data-processing-inc-nasdaqadp-vp-sells-stock-for-57544-20/ Wed, 05 Oct 2022 16:34:33 +0000 https://eaglerock-is.com/automatic-data-processing-inc-nasdaqadp-vp-sells-stock-for-57544-20/ Vice President Laura G. Brown, also a shareholder of Automatic Data Processing, Inc., listed 252 shares of her company for sale during the Oct. 3 trading session (NASDAQ: ADP). The transaction involved the sale of the shares at an average price of $228.35 per share, which resulted in a total sale volume of $57,544.20. As […]]]>

Vice President Laura G. Brown, also a shareholder of Automatic Data Processing, Inc., listed 252 shares of her company for sale during the Oct. 3 trading session (NASDAQ: ADP). The transaction involved the sale of the shares at an average price of $228.35 per share, which resulted in a total sale volume of $57,544.20. As a result of the transaction, the vice president now owns 6,016 shares of the company. Based on the current stock price, this gives the Vice President a total wealth of approximately $1,373,753.60. If you follow this link, you will be redirected to the SEC filing where the transaction was discussed in more detail. Deposit $100 and get $110 to trade stocks
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Automatic Data Processing (NASDAQ: ADP) released its latest earnings report on July 27, and the report was well received. The business services provider reported earnings per share for the quarter of $1.50, $0.02 higher than the consensus estimate of $1.48. The return on equity for automatic data processing was calculated at 66.25%, while the company’s net margin was calculated at 17.87%. Contrary to the $4.05 billion in sales that relevant industry professionals predicted the company would achieve in the quarter, the company generated $4.13 billion in revenue during this period. The company reported earnings of $1.20 per share, a 20% increase over results reported for the same quarter a year earlier. Compared to the same quarter of the previous year, the increase in turnover was 10.5% higher than before. Sell-side analysts predict Automatic Data Processing, Inc. will generate $8.05 per share in revenue in 2018.
Additionally, the company recently announced and paid a quarterly dividend, which was done on the first of this month, October, and was paid to shareholders. On Friday, September 9, dividends of $1.04 were distributed to owners who still held their shares. This took place after the distribution date of the previous Friday, September 2. This equates to a dividend payment of $4.16 per year and a 1.76% return on investment. The start of the ex-dividend period took place on Thursday 8 September. 59.34% of Automatic Data Processing Corporation’s revenue is paid out as dividends.

ADP’s stock price rose $4.37 in Tuesday’s trading session, bringing the company’s total to $236.62 at the end of the day. The total number of company shares that changed hands was 1,940,998, which is higher than the average daily share volume of 1,842,571 shares. Over the previous 52 weeks, the price of a share of Automatic Data Processing, Inc. ranged from a low of $192.26 to a high of $261.59. The general liquidity ratio is currently 0.99, while the current and debt-to-equity ratios are both 0.93. The debt ratio is currently 0.93. All of the factors that contribute to the company’s current valuation of $98.27 billion are as follows: the company has a beta of 0.83, a PE ratio of 33.13 and a PEG ratio of 2 ,34. The company had a simple moving average of $226.87 over the past 200 days, while the simple moving average over the past 50 days was $242.53.

As a result of recent events, several large investors have changed the proportion of company shares they currently hold in their portfolios. BlackRock Inc. increased the percentage of automatic data processing shares it held by 5.1% in the first three months. BlackRock Inc. now owns 33,637,473 shares of the business services provider after purchasing an additional 1,642,852 shares during the period in question. This gives the company a market value of $7,653,871,000 due to the shares currently outstanding. Additionally, Automatic Data Processing’s percentage of shares in Charles Schwab Investment Management Inc. increased 7.4% in the first quarter after the company purchased additional shares. Charles Schwab Investment Management Inc. now owns 6,689,136 shares of the business services provider after buying an additional 461,438 shares in the most recent period. The value of these shares, added to the value of the other assets of the company, amounts to a total of $1,522,047,000. In the first three months of 2018, Capital World Investors was able to amass an additional 16.9% of automatic data processing shares, bringing the total share percentage of this company to 26.1%. After making 779,457 additional share purchases during the quarter, Capital World Investors now owns a total of 5,393,160 shares of the business services provider. These shares have a combined value of a total of $1,227,160, bringing the company’s overall investment to $1,227,160. In the first three months of 2018, Capital Research Global Investors bought an additional 10.5% of automatic data processing shares. This purchase brought the total percentage of ADP shares held by the company to 75%. Following the acquisition of an additional 364,087 shares of the business services provider’s stock last quarter, Capital Research Global Investors now owns 3,839,498 shares of the company’s stock. The current market value of these shares is $873,639,000.
Last but not least, during the second quarter, Legal & General Group Plc increased the amount of its automatic data processing inventory held by 3.3%. This should certainly not be considered the least important development. Following the acquisition of an additional 101,869 shares during the period in question, Legal & General Group Plc now owns 3,192,438 shares in the capital of the business services provider. The value of Legal & General Group Plc’s holdings in the business services provider’s stock is estimated at $670,539,000. Currently, institutional investors, such as hedge funds and other types of institutional investors, own 79.06% of the company’s shares.

Many investment research analysts have recently focused their efforts on ADP shares. In a research note released Thursday, July 28, Morgan Stanley raised its rating for automatic data processing from “equal weight” to “overweight” and raised its price target for the company’s stock by $235.00. at $245.00 in a research note. Barclays raised its price target for automatic data processing on Tuesday (August 9) in a publicly available research report. The new price target is $280.00. Following the release of their analysis on Tuesday, September 20, Cowen raised its price target for Automatic Data Processing from $230.00 to $236.00. The new price target can be found here. Following the release of their analysis on Tuesday, September 20, Cowen raised its price target for Automatic Data Processing from $230.00 to $236.00. The new price target can be found here. Wolfe Research lowered its price target for automatic data processing from $235.00 to $210.00 in a study released Wednesday, July 20. The stock was recommended to “hold” by nine analysts, while two additional analysts recommended the stock to “buy.” Most research companies currently have a “Hold” rating for automatic data processing, and the average price target they have set for the company is $236.85. These details were obtained from Bloomberg.

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Custom data processing partners with Yellowbrick to deliver https://eaglerock-is.com/custom-data-processing-partners-with-yellowbrick-to-deliver/ Tue, 04 Oct 2022 13:00:00 +0000 https://eaglerock-is.com/custom-data-processing-partners-with-yellowbrick-to-deliver/ MOUNTAIN VIEW Calif., Oct. 04, 2022 (GLOBE NEWSWIRE) — Yellowbrick Data, the leading multi-cloud data warehouse provider, today announced that Custom Data Processing Inc. (CDP), a national provider of software solutions for federal, state and local public health organizations, chose Yellowbrick to manage its growing data volumes. With Yellowbrick, CDP customers and public sector agencies […]]]>

MOUNTAIN VIEW Calif., Oct. 04, 2022 (GLOBE NEWSWIRE) — Yellowbrick Data, the leading multi-cloud data warehouse provider, today announced that Custom Data Processing Inc. (CDP), a national provider of software solutions for federal, state and local public health organizations, chose Yellowbrick to manage its growing data volumes. With Yellowbrick, CDP customers and public sector agencies make better decisions by analyzing large amounts of data faster, in the cloud or on-premises, as required by government policies, leveraging Yellowbrick’s unique capability to deploy anywhere.

“The pandemic has resulted in an increase in government health data – not only for health agencies, but also for national nutrition programs,” said Scott Pralle, vice president of business development at CDP. “CDP manages the sensitive data that allows these essential programs to operate. Yellowbrick’s high performance data warehouse stood out from the competition and was the best choice for our public sector customers. Yellowbrick’s performance and flexibility allows us to quickly slice and dice our data to better leverage our time, build robust reports and dashboards, and deliver better results to our clients.

CDP’s Data Direct solution is a one-stop-shop for public health data analytics. Programs such as WIC (Women, Infants and Children), EMR (Electronic Medical Records), Environmental Health, and SNAP (Supplemental Nutrition Assistance Program) rely on Data Direct to gain insights and help manage programs by enforcing a evidence-based decision making. Data Direct democratizes relevant data to user groups at national, local and public levels.

Data Direct assists “power users” with ad hoc drag-and-drop reports and those who simply want to answer questions about their data. CDP’s Yellowbrick multi-node data warehouse allows CDP to scale to large volumes of data while dramatically improving performance. Tableau and Yellowbrick integration powers new analytical capabilities in data stores using direct live queries, making data available as soon as it is loaded into the warehouse.

“Many companies and agencies are still trying to manage the mountains of data created during the pandemic. With Yellowbrick, CDP can deploy its solution wherever its customers want, in public or private clouds,” said Mark Cusack, CTO at Yellowbrick. “We are excited to see how Yellowbrick will positively impact the public health programs that CDP serves.”

About Custom Data Processing, Inc.
Custom Data Processing, Inc. (CDP) has been providing electronic health solutions to federal, state, and local health organizations since 1979. CDP’s highly agile, custom software solutions, built around core system components, are continually improved based on industry trends and customer feedback. These solutions have been implemented in over a thousand locations across the United States. CDP offers three distinct offerings for WIC programs, including management information solutions (MIS), electronic benefit processing (WIC Direct), and a data warehouse tool (Data Direct). Additional offerings include an environmental health app, electronic health records and networking services. For more information about CDP, visit www.cdpehs.com. Follow CDP on Twitter @CDPEHS.

About Yellowbrick Data
Yellowbrick Data Warehouse is a modern, elastic data warehouse with separate storage and compute that runs in the cloud and on-premises. Yellowbrick enables large enterprises to eliminate complexity, reduce risk, and predict and control costs by running all their data anywhere, on multi-cloud instances.

Yellowbrick enables enterprises to run complex queries against petabyte-scale live data in their own cloud account, while supporting high concurrency with fast, interactive response to customers’ toughest business questions. Yellowbrick Data was founded in 2014 and is based in Mountain View, California. Learn more at yellowbrick.com and visit us on LinkedIn and Twitter.

Media Contact
Glen Zimmerman
Yellowbrick Data
press@yellowbrick.com

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Smart Cities India Real Time Data Processing Iot Ai Machine Learning 5g Advantages https://eaglerock-is.com/smart-cities-india-real-time-data-processing-iot-ai-machine-learning-5g-advantages/ Fri, 30 Sep 2022 09:09:57 +0000 https://eaglerock-is.com/smart-cities-india-real-time-data-processing-iot-ai-machine-learning-5g-advantages/ The National Smart Cities Mission (SCM) was launched by the Government of India on June 25, 2015, with the aim of improving the quality of life and accelerating growth in the urban sector. Through a two-stage competition, 100 cities were selected to participate in this unique program. These cities would change for the better with […]]]>

The National Smart Cities Mission (SCM) was launched by the Government of India on June 25, 2015, with the aim of improving the quality of life and accelerating growth in the urban sector. Through a two-stage competition, 100 cities were selected to participate in this unique program. These cities would change for the better with improved infrastructure, the application of technologies such as artificial intelligence (AI), machine learning (ML), and real-time monitoring within government systems.

As population and urbanization continue to grow, many cities will look to modern technologies and advanced networks to help them manage resource shortages. Governance in cities will increasingly take advantage of the Internet of Things (IoT) through the use of “smart city solutions”.

IoT: smart, scalable and strategic solution

Using technology in scaling a city requires smart, connected networks that can process data seamlessly. The Internet of Things (IoT) is an “intelligent” solution that accompanies these technological developments. The use and development of IoT has increased in recent years, and a study by IoT Analytics predicts that there will be approximately 27 billion IoT devices linked by 2025.

ALSO READ: What is IoT? How it works? How does it improve our daily life?

The applicability of IoT relates to a range of applications including smart homes, parking, water monitoring, healthcare, road lighting, smart waste management, etc. Any comprehensive IoT strategy for creating smart cities must start with a database. Modern databases automate the dissemination of information from massive amounts of rapidly changing data points to enable intelligent real-time decision making.

Making cities smart in real time

Real-time data processing is crucial to solving the “smart cities” puzzle. Real-time data platforms analyze large volumes of city-scale data collected through a network of IoT systems. All data is ingested and processed in real time, from gigabyte to petabyte.

It is essential that huge amounts of data be processed in less than a millisecond and without error. To improve infrastructure, for example public lighting, roads and public spaces for citizens, it is essential to feed a fast and intelligent data flow for optimal urban services in the following areas:

Smart Energy: IoT sensors will drive the adoption of smart power distribution, dynamically-read electricity meters, self-healing energy networks, networked buildings and industrial facilities, automated water use and leak detection, and just-in-time waste collection.

Environmental controls and sustainability: IoT sensors would help maximize energy efficiency, pollution monitoring, traffic control, and sustainable resources. IoT sensors provide data on how to reduce emissions and eliminate waste. They enable long-term sustainability solutions when combined with in-depth and accurate analysis of real-time data.
Smart Buildings – IoT-enabled facility management solutions connect building-wide sensors to improve energy efficiency and space utilization at lower cost.

Mobility and connected transport: Monitored transit systems are safer and cleaner with coordinated transit systems, traffic control, parking and many other transit-related services that rely on real-time data on moving traffic, parking spaces and predictive information for road management.

Public Safety and Security: The essential characteristic of a smart city is to provide inhabitants with safer and better living conditions. Real-time cameras and video surveillance systems help reduce crime through motion detection and real-time crowdsourcing of crime data, including identifying security breaches, active crime tracking and speeding up response times from authorities.

5G powers the IoT

What does 5G mean for the IoT? How exactly does 5G achieve higher data rates? The advancement of everything from self-driving cars to smart grids for renewable energy to AI-enabled robots on manufacturing floors is made possible by the faster, more reliable and more secure connectivity of 5G. With the right speed, latency, and cost trade-offs, networks can support billions of connected devices in the vast IoT ecosystem.

5G and IoT are expected to generate around 1 billion terabytes of data by 2025. Current statistics predict that the volume of data generated will rise to 181 zettabytes by 2025, more than six times the amount processed in 2018.

With 5G we will have faster connections, more reliability and greater capacity at lower cost, enabling the high bandwidth and low latency needed for smart city applications such as real-time connected vehicles and data traffic and infrastructure security.

It also enables huge advancements in critical technology areas, from artificial intelligence (AI) and machine learning (ML) to video surveillance, IoT and self-driving cars.

The introduction of emerging technologies such as IoT, AI and automation will catalyze the development of smart cities, but this growth will only succeed with the processing and analysis of 5G data on modern data platforms in real time.

These platforms can move large amounts of data across the network and create an affordable way to store data so it can be easily accessed and analyzed.

How ‘smart’ is India getting?

The knowledge gained through real-time data analysis is crucial to creating livable and resource-efficient cities.

We need instant and accurate data analytics to make sense of huge volumes of data from many sources, such as geospatial data, traffic data, pedestrian traffic data, vehicle count data, crime statistics, etc.

As data must be ingested, stored and computed in real time, managing this vast volume of data and managing the continuous increase in data are important issues that impact the development of smart cities.

An increase in the amount of data forms, such as social media, audio, video, and smart device data, has coincided with the growth of unstructured data. Organizations must be aware of and prepared with the tools, capabilities, and information needed to work with complex data in real time.

The ability of entities to share and analyze data determines the success of a smart city. For all companies and organizations to create software solutions and applications that support automation and create an “intelligent” infrastructure, they must instantly exchange critical information.

Currently, many cities are vying to become smart cities in hopes of reaping some of their economic, environmental, and social benefits. Therefore, they might consider opportunities made possible by the use of data analytics in smart city applications.

Real-time data management and processing capabilities can enable a new ecosystem of services, with data-driven governments and information-driven policies, and improve government operational efficiency.

As more and more Indians move from villages to towns and then to cities, India must embrace emerging innovations such as sensors, earth observation, cloud analytics, visualization data, data science, citizen science, IoT, etc., to create better and more efficient smart cities of the future.

(The author is Vice President – Asia-Pacific and Japan at Aerospike, which is a real-time data platform that allows organizations to instantly act on billions of transactions while reducing server footprint by up to ‘at 80%.)

Disclaimer: The opinions, beliefs and views expressed by the various authors and forum participants on this website are personal.

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Navy asks L3Harris to provide signal data processing for onboard network that mixes sensors and weapons https://eaglerock-is.com/navy-asks-l3harris-to-provide-signal-data-processing-for-onboard-network-that-mixes-sensors-and-weapons/ Fri, 23 Sep 2022 07:42:40 +0000 https://eaglerock-is.com/navy-asks-l3harris-to-provide-signal-data-processing-for-onboard-network-that-mixes-sensors-and-weapons/ WASHINGTON- US Navy surface warfare experts required signal data processors and spare parts for the Cooperative Engagement Capability (CEC) tactical network aboard Navy surface warfare vessels. They found their solution at L3Harris Technologies. Naval Sea Systems Command officials in Washington last week announced a $32 million order from the L3Harris C5 Integrated Systems Segment in […]]]>

WASHINGTON- US Navy surface warfare experts required signal data processors and spare parts for the Cooperative Engagement Capability (CEC) tactical network aboard Navy surface warfare vessels. They found their solution at L3Harris Technologies.

Naval Sea Systems Command officials in Washington last week announced a $32 million order from the L3Harris C5 Integrated Systems Segment in Camden, NJ, for CEC spares and signal data processors.

The CEC is a network of maritime tactical sensors and weapons for anti-aircraft warfare that combines information from sensors on aircraft and surface ships that operate over widely distributed geographic areas.

The CEC combines sensor information into a common tactical picture for battle groups at sea. It improves overall situational awareness and enables fleet commanders to work closely together to attack enemy forces at long range.

Related: BAE Systems to Develop Network Management Software to Link Sensors and Weapons on Land, Air and Sea

The order from L3Harris is a modification of a six-year, $14.9 million contract the company won last July for the production and repair of the CEC system. This contract includes options that could increase its value to $378.9 million.

The CEC combines sensors and weapons in an integrated real-time network that expands the battlespace; improves situational awareness; increases the depth of shot; allows long intercept ranges; and improves decision and reaction times.

It extracts and distributes sensor information so that the superset of this data is available to all participating CEC-equipped units by merging distributed data from Land Mobile Units of the Onboard Composite Tracking Network, Airborne, Joint Land Attack Cruise Missile Defense Elevated Netted Sensor System (JLENS) and coalition partners in a single fire control quality air track image.

The system uses line-of-sight data distribution to share radar measurement data between sensors and weapons to create an integrated distributed aerial picture. It combines surveillance and targeting information in such a way that the combined system is greater than the sum of its parts.

Related: CACI Joins Networking Software Project to Connect Sensors and Weapons in New Brand of Tiled Warfare

The jam-resistant CEC obtains target trajectory information to form a composite trajectory in real time to help coordinate theater air and missile defense to engage incoming cruise missiles.

The CEC includes the Data Distribution System (DDS), the Cooperative Engagement Processor (CEP), and the interface to combat systems and sensors.

The DDS encodes and distributes sensor and vessel engagement data. CEP processes near real-time data force levels and allows surface warships and other weapons platforms to instruct their onboard sensors and weapons to engage targets without actually tracking them. .

On this order, L3Harris will perform the work in Lititz and Lancaster, Pennsylvania; Salt Lake City; and Largo, Florida, and is expected to be complete by April 2023. For more information, contact L3Harris C5 Integrated Systems online at www.l3harris.comor Naval Sea Systems Command at www.navsea.navy.mil.

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