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Advanced and Predictive Analytics Market 2022 by Keyplayers and Vendors: International Business Machines Corporation (IBM), SAS Institute Inc.,…

May 23, 2022 | Author: admin

This report focuses on potential global competitiveness of Global Advanced and Predictive Analytics Market industry. The report unearths the determinants of the export competitiveness of global Advanced and Predictive Analytics market. The report provides study of the individual leading firms engaging in Advanced and Predictive Analytics products exports. The raw material scenario, quality of demand, market share, and competitiveness of global Advanced and Predictive Analytics market is evaluated in the report. The local market scenario, quality of demand, export significance, and advantages of export competitiveness are discussed in the report.

Key Players in the Advanced and Predictive Analytics market:

International Business Machines Corporation (IBM)SAS Institute Inc.Microsoft CorporationSAP AGTableau Software Inc.Information Builders, Inc.Fair Isaac Corporation (FICO)Teradata CorporationAcxiom CorporationOracle CorporationTIBCO Software Inc.

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The report also provides a sneak peak into the global trade statistics, production, consumption, and other crucial aspects of the market important for market players to understand as well as affecting the development of the global Advanced and Predictive Analytics market. The report provides a thorough assessment of the global Advanced and Predictive Analytics market taking into account the key factors driving or limiting the growth of the global Advanced and Predictive Analytics market during the analysis period. The report highlights opportunities available in the global Advanced and Predictive Analytics markets sub markets along with comprehensive analysis of the competitive landscape.

The report provides supply side estimates, demand for products and services in local and international markets, estimates of future, market size estimates, information on the key companies in the global Advanced and Predictive Analytics market. The key companies are detailed in the report proving their product profiles, new products, upcoming offerings, competitive pricing, and other details of the companies are included in the report. The analysts have studied those segments of the global Advanced and Predictive Analytics market that are poised for rapid expansion in forecast timeframe 2022-2029. The report has provided this estimates and possibilities with the help of meticulous comparison of the past records and present data.

Advanced and Predictive Analytics Market Types:

Data MiningStatisticalTesting Analytics

Advanced and Predictive Analytics Market Applications:

Banking and Financial ServicesInsuranceGovernment, Public Administration and UtilitiesPharmaceuticalsTelecom and IT predictiveRetail (Consumer Goods)Transportation and LogisticsOthers

The report provides regional outlook of the global Advanced and Predictive Analytics market and the details of the market size stretches across South East Asia, Middle East & Africa, South America, Asia-Pacific, Europe, and North America. The report measures the economic performance of these regions in Advanced and Predictive Analytics market, their contribution to overall growth of Advanced and Predictive Analytics market, and assesses the impact of these regions on the overall growth of the industry. The report also analyses the consumption growth rate of every region in the study duration, export potential, trade statistics, and other regulations related to Advanced and Predictive Analytics marketing and production. This data is validated through statistical data. The report provides records of the sales, overall revenue witnessed by each product type and further details are provided in the report.

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Advanced and Predictive Analytics Market 2022 by Keyplayers and Vendors: International Business Machines Corporation (IBM), SAS Institute Inc.,...

Second-largest indicated-or-better rare earth resource in the US now identified – MINING.COM – MINING.com

May 23, 2022 | Author: admin

According to the 2022 feasibility study, the Elk Creek project contains an estimated 632.9 kilotonnes of contained total rare earth oxides in the indicated mineral resource category. According to US Geological Survey data, this places the Elk Creek mineral resource behind MP Materials Mountain Pass deposit in the US but ahead of all other current rare earth projects in terms of contained TREO from a NI 43-101 rare earth resource of indicated or higher classification, NioCorp said in a media statement.

The company pointed out that the 2022 feasibility study also showed that, in addition to relatively high grades of niobium, scandium, and titanium, the Elk Creek mineral resource contains various amounts of all REEs.

There is potential for NioCorps REEs to be mined, crushed, and placed into solution as part of the process NioCorp plans to use to produce its primary niobium, scandium, and titanium products once project financing is secured, the release states. Depending upon the outcome of metallurgical testing on REE recovery rates from Elk Creek ore, now being conducted at a demonstration plant in Quebec, and whether necessary project financing is secured, NioCorp could produce separated rare earths as a byproduct, placing it at a competitive advantage vis--vis other rare earth projects.

Given these results, the Colorado-based firm plans to commission a new technical report on the Elk Creek project in accordance with NI 43-101.

Using a $180/tonne NSR cut-off that was calculated using solely the contained niobium, scandium, and titanium in the mineral resource, the 2022 feasibility study showed that the Elk Creek Indicated Mineral Resource includes:

In order to update the projects mineral resource to include REE data, NioCorp and its consultants were required to complete additional assays of historical drill core to fill data gaps in the existing resource database and re-model the mineral resource. The mine plan and mineral reserve were also updated, independent of the REE data collection and REE by-product mineral resource.

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Second-largest indicated-or-better rare earth resource in the US now identified - MINING.COM - MINING.com

Mining companies in Goa asked to take care of ‘pits’ – Investing.com India

May 23, 2022 | Author: admin

Panaji, May 23 (IANS) Admitting that his department will not be in a position to manage any mishap, Goa's Water Resources Department (WRD) Minister Subhas Shirodkar said that Mining companies have been asked to take care of 'pits' during the monsoon season.

Shirodkar, speaking to media persons here, said that his department won't be able to manage these pits all of a sudden. "We can drain out water, but if a landslide occurs then we won't be able to manage it. Hence mining companies are told to take care of it," the WRD minister said.

The state government has recently started the process to take over 88 mining leases by issuing notices to vacate the leases by June 6. Some of the companies while vacating had also started to remove water pumps from pits. However, now they have been asked to take adequate measures to manage pits.

"Mining pits come under the Mining Ministry. The Chief Minister is handling the issue," Shirodkar said.

He said that his department will monitor the situation.

Chief Minister Pramod Sawant had recently said that if mining companies fail to adhere to the request then Water Resources Department (WRD) and Public Works Department (PWD) will take care of the issue.

Mining companies have been asked to maintain the mining pits this year.

--IANS

sanjay/skp/

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Mining companies in Goa asked to take care of 'pits' - Investing.com India

Russia dominates nuclear power supply chains and the West needs to prepare now to be independent in the future – CNBC

May 23, 2022 | Author: admin

Wind turbine and cooling towers of the Cruas-Meysse nuclear power plant in France, April 12, 2021.

Jean-Marie HOSATTE | Gamma-Rapho | Getty Images

Russia's war in Ukraine has pushed countries around the globe to wean themselves from Russian oil and natural gas.

Parallel conversations are imminent in the nuclear energy space, too, because Russia is also a dominant player in global supply chains of nuclear reactor technology, as is detailed by a new paper published Monday from Columbia University's Center on Global Energy Policy.

There were 439 nuclear reactors in operation around the globe in 2021, and 38 of them were in Russia, an additional 42 were made with Russian nuclear reactor technology, and 15 more under construction at the end of 2021 were being built with Russian technology.

Reducing or eliminating dependence on nuclear supply chains from Russia will vary by country and need.

If a country has not yet constructed nuclear reactors, then they can, from the beginning, decide not to contract with Russia. The U.S., France, Korea and China are "viable" supplier options, according to the paper.

Second, if a country already has Russian nuclear reactor models, VVERs, then probably looks to Russia for repair parts and services. (VVER stands for 'water-water energy reactor'in Russian, which is vodo-vodyanoi enyergeticheskiy reaktor in Russian, ergo the acronym.) In this case, countries can get repair assistance from Westinghouse, which is headquartered in Pennsylvania, according the the report.

Then there is the issue of fuel. Nuclear fission reactors are fueled with enriched uranium.

Russia mines approximately 6% of the raw uranium produced annually, according to the report. That's an amount that can be replaced if other countries that mine uranium increase their uranium mining.

However, uranium does not go directly from a mine into a nuclear reactor. It has to go through conversion and enrichment before it can be used as fuel in a nuclear reactor.

Here, Russia is a dominant player. Russia owned 40% of the total uranium conversion infrastructure in the world in 2020, and 46% of the total uranium enrichment capacity in the world in 2018, according to the report. (This was the most up-to-date data publicly available, according to the report authors.)

This is where the U.S. and allied countries would need to focus their attention, according to the report, which was co-authored by Paul Dabbar, a former under secretary of Energy for Science at the Department of Energy, and Matthew Bowen, a research scholar at Columbia's Center on Global Energy Policy.

Besides Russia, these uranium conversion and enrichment capabilities exist in Canada, France, Germany, the Netherlands, the United Kingdom and the United States.

Those capacities "are enough to replace at least some" of the conversion and enrichment that Western nuclear reactors need, but it's not clear that the capacity will be able to fully replace the Russian capacity.

The U.S. also needs to be prepared for fuel that goes into advanced reactors, which are currently in development, and require uranium enriched to 15 to19.75%, where conventional light water reactors that are currently in operation in the United States use uranium enriched to between 3 to 5 %.

This high-assay low-enriched uranium (HALEU) fuel is currently only available at a commercial scale from Russia, according to the report.

"More investment in mining, conversion, and enrichment facilities may be necessary to fully extricate Western nuclear fuel chains from Russian involvement, Dabbar and Bowen write in their report. "However, adding sufficient new conversion capacity and enrichment capacity will take years to accomplish."

But to convince private companies to dedicate money and resources to uranium infrastructure, they need the government to commit to not reverting to Russian supplies.

"Their worry will be that in a year or two, perhaps less, Russian uranium products will be allowed back into national markets and will undercut them, causing them to lose out on their investments," Dabbar and Bowen said.

In the United States, there is only one uranium conversion facility it's in Metropolis, Illinois and it has been on standby since November 2017. Its reopening is "pending market improvement and customer support," according to a power point presentation from the partnership between General Atomics and Honeywell that operates the plant, ConverDyn. It won't be able to return to operability until 2023, when it could convert 7,000 tons of uranium per year. To ramp up to 15,000 tons per year, it will take the one plant longer than 2023.

Therefore, Dabbar and Bowen said it would be prudent for the United States to wean off Russian confinement capacity "a period of years not months."

Russia dominates nuclear power supply chains and the West needs to prepare now to be independent in the future - CNBC

IoT in Healthcare Market is projected to grow at a CAGR of 18.0%, reaching US$ 952.3 Billion by 2032 – Digital Journal

May 23, 2022 | Author: admin

[297 Pages Report] The globalIoT in healthcare marketis projected to reach US$ 181.4 Billion in 2022, anticipated to grow at a CAGR of 18.0%, reaching US$ 952.3 Billion by 2032. The market is slated to document a Y-o-Y growth rate of 20.7% from 2021-2022, increasing from the previously registered value of US$ 150.3 Billion.

By enabling real-time patient data access and remote patient monitoring, the Internet of Things (IoT) has the potential to disrupt traditional paper-based healthcare therapy. With the emergence of this digital healthcare technology, the impending need for enhanced diagnostics and targeted therapeutic options was met.

Furthermore, it not only enables physicians to remotely monitor patients, but it also functions as a fitness and wellness tracker for athletes and a dose reminder for patients. The successful implementation of IoT in remote monitoring of diabetic and asthma patients, along with the growing usage of fitness and wellness devices, has resulted in a considerable demand for the IoT healthcare business.

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Key Takeaways from the Market StudyIoT in healthcare experienced a growth rate worth 18.8% between 2015 and 2021

Portable diagnostic devices in the IoT in Healthcare segment to expand at a CAGR of 10.1% during the forecast period

In the U.S., the market is predicted to reach US$ 208.1 Billion while growing at a CAGR of 18.9% during the forecast period

Chinas market is expected to reach a market value of US$ 92.8 Billion with a CAGR of 19.5% during the forecast period

Big data analytics is an area of IoT that is quickly expanding. The most recent breakthroughs in machine learning, logical procedures, computational intelligence, and data mining are required for big data analytics, says an FMI analyst.

Competitive Landscape

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Key players that have been profiled in the report are Apple Inc., Cisco Systems Inc., GE Healthcare Ltd., Google (Alphabet), International Business MachinesCorporation, Medtronic PLC, Microsoft Corporation, Proteus Digital Health, Koninklijke Philips N.V., QUALCOMM Incorporated, and Abbot Laboratories are among companies that offer products and technologies that will allow customers to take advantage of new technologies.

In April 2019, Royal Philips and Spencer Health Solutions expanded their relationship to provide chronically sick patients in selected European Union (EU) nations with in-home medication adherence and the Philips telehealth platform.

Medtronic worked with IBM Watson in January 2019 to provide IQcast, a new feature of its current product Sugar.IQ, for iOS mobile devices in the United States. The software would provide patients with a hypoglycemic episode to monitor their low glucose level by anticipating the occurrence 1 to 4 hours in advance.

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Future Market Insights (ESOMAR certified market research organization and a member of Greater New York Chamber of Commerce) provides in-depth insights into governing factors elevating the demand in the market. It discloses opportunities that will favor the market growth in various segments on the basis of Source, Application, Sales Channel and End Use over the next 10-years.

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IoT in Healthcare Market is projected to grow at a CAGR of 18.0%, reaching US$ 952.3 Billion by 2032 - Digital Journal

The Worldwide Jewelry Industry is Expected to Reach $459 Billion by 2030 – GlobeNewswire

May 23, 2022 | Author: admin

Dublin, May 20, 2022 (GLOBE NEWSWIRE) -- The "Jewelry Market Share, Size, Trends, Industry Analysis Report, By Product; By Material Type; By Category; By Distribution Channel; By Region; Segment Forecast, 2022 - 2030" report has been added to ResearchAndMarkets.com's offering.

The global jewelry market size is expected to reach USD 459.43 billion by 2030, according to a new study. The report gives a detailed insight into current market dynamics and provides analysis on future market growth.

Ornaments have gained traction in the emerging market due to lifestyle changes and a rise in the prices of precious metal ornaments, contributing to the growth of the industry size. Also, female consumers' increased fashion consciousness and increased acceptance of pieces of ornaments such as necklaces, rings, and bracelets support the growth of the industry. Further, rising investment in jewelry development, rising partnerships, and geographical expansion by the major players drive industry growth.

For instance, Malbar Group would spend Rs. 750 crore (US$ 100 Billion) in a gold refining and jewelry business in Hyderabad in September 2021. Malabar Gold & Diamonds said in April 2021 that it would invest Rs. 1,600 crore (US$ 214 Billion) in FY22 to open 56 outlets, 40 of which would be in India and 16 in international markets.

Moreover, Tanishq will launch antimicrobial jewelry in select areas as a trial project in June 2021. In addition to it, the World Gold Council and the Gem and Jewellery Export Promotion Council struck an agreement in June 2021 to produce gold ornaments in India. In March 2021, Joyalukkas partnered with IBM to design, build, and deploy a cloud-based e-commerce platform across 11 countries. However, obstacles impeding industry growth include rising raw material prices for ornaments, changes in ornaments packaging patterns, and the product's short-term appeal. Thus, these factors are boosting the market growth during the forecast period.

Based on the product, the ring segment accounted for the leading share in the market in 2021. The increased customer interest in the exquisite designs and features of the rin30gs is the primary cause for this jewelry's success. Rings are also thought to be fashionable and elegant. As a result, increased consumption of men's signet rings is likely to drive the industry.

Rings come in a variety of sizes and forms. They are used not only during engagements and anniversaries but also regularly. Silver, for example, is believed to have healing powers and assist with heat production and circulation. As a result, many people are wearing silver rings. The accessibility of custom-made rings and increased awareness of the religious benefits of various metals are predicted to drive the ring product segment throughout the forecast period.

Market players such as Buccellati, Cartier, Chow Tai Fook Jewelry Company Limited, LVMH Group, Malabar Gold & Diamonds, Swarovski, Tata Sons Private Ltd, The Swatch Group AG, are some key players operating in the global market.

Key Topics Covered:

1. Introduction

2. Executive Summary

3. Research Methodology3.1. Overview3.1.1. Data Mining3.2. Data Sources3.2.1. Primary Sources3.2.2. Secondary Sources

4. Global Jewelry Market Insights4.1. Jewelry - Industry Snapshot4.2. Jewelry Market Dynamics4.2.1. Drivers and Opportunities4.2.1.1. Increasing disposable income4.2.1.2. Changing lifestyles and perception of jewelry4.2.2. Restraints and Challenges4.2.2.1. High cost4.3. Porter's Five Forces Analysis4.3.1. Bargaining Power of Suppliers (Moderate)4.3.2. Threats of New Entrants: (Low)4.3.3. Bargaining Power of Buyers (Moderate)4.3.4. Threat of Substitute (Moderate)4.3.5. Rivalry among existing firms (High)4.4. PESTLE Analysis4.5. Jewelry Industry Trends4.6. Value Chain Analysis4.7. COVID-19 Impact Analysis

5. Global Jewelry Market, by Product5.1. Key Findings5.2. Introduction5.2.1. Global Jewelry Market, by Product, 2018 - 2030 (USD Billion)5.3. Necklace5.3.1. Global Jewelry Market, by Necklace, by Region, 2018 - 2030 (USD Billion)5.4. Ring5.4.1. Global Jewelry Market, by Ring, by Region, 2018 - 2030 (USD Billion)5.5. Earrings5.5.1. Global Jewelry Market, by Earrings, by Region, 2018 - 2030 (USD Billion)5.6. Bracelet5.6.1. Global Jewelry Market, by Bracelet, by Region, 2018 - 2030 (USD Billion)5.7. Others5.7.1. Global Jewelry Market, by Others, by Region, 2018 - 2030 (USD Billion)

6. Global Jewelry Market, by Material Type6.1. Key Findings6.2. Introduction6.2.1. Global Jewelry Market, by Material Type, 2018 - 2030 (USD Billion)6.3. Silver6.3.1. Global Jewelry Market, by Silver, by Region, 2018 - 2030 (USD Billion)6.4. Gold6.4.1. Global Jewelry Market, by Gold, by Region, 2018 - 2030 (USD Billion)6.5. Platinum6.5.1. Global Jewelry Market, by Platinum, by Region, 2018 - 2030 (USD Billion)6.6. Diamond6.6.1. Global Jewelry Market, by Diamond, by Region, 2018 - 2030 (USD Billion)6.7. Others6.7.1. Global Jewelry Market, by Others, by Region, 2018 - 2030 (USD Billion)

7. Global Jewelry Market, by Category7.1. Key Findings7.2. Introduction7.2.1. Global Jewelry Market, by Category, 2018 - 2030 (USD Billion)7.3. Branded7.3.1. Global Jewelry Market, by Branded, by Region, 2018 - 2030 (USD Billion)7.4. Unbranded7.4.1. Global Jewelry Market, by Unbranded, by Region, 2018 - 2030 (USD Billion)

8. Global Jewelry Market, by Distribution Channel8.1. Key Findings8.2. Introduction8.2.1. Global Jewelry Market, by Distribution Channel, 2018 - 2030 (USD Billion)8.3. Offline8.3.1. Global Jewelry Market, by Offline, by Region, 2018 - 2030 (USD Billion)8.4. Online8.4.1. Global Jewelry Market, by Online, by Region, 2018 - 2030 (USD Billion)

9. Global Jewelry Market, by Geography

10. Competitive Landscape10.1. Expansion and Acquisition Analysis10.1.1. Expansion10.1.2. Acquisitions10.2. Partnerships/Collaborations/Agreements/Exhibitions

11. Company Profiles11.1. Buccellati11.1.1. Company Overview11.1.2. Financial Performance11.1.3. Product Benchmarking11.1.4. Recent Development11.2. Cartier11.2.1. Company Overview11.2.2. Financial Performance11.2.3. Product Benchmarking11.2.4. Recent Development11.3. Chow Tai Fook Jewelry Company Limited11.3.1. Company Overview11.3.2. Financial Performance11.3.3. Product Benchmarking11.3.4. Recent Development11.4. LVMH Group11.4.1. Company Overview11.4.2. Financial Performance11.4.3. Product Benchmarking11.4.4. Recent Development11.5. Malabar Gold & Diamonds11.5.1. Company Overview11.5.2. Financial Performance11.5.3. Product Benchmarking11.5.4. Recent Development11.6. PANDORA JEWELRY LLC11.6.1. Company Overview11.6.2. Financial Performance11.6.3. Product Benchmarking11.6.4. Recent Development11.7. SHR Jewelry Group11.7.1. Company Overview11.7.2. Financial Performance11.7.3. Product Benchmarking11.7.4. Recent Development11.8. Swarovski11.8.1. Company Overview11.8.2. Financial Performance11.8.3. Product Benchmarking11.8.4. Recent Development11.9. Tata Sons Private Ltd.11.9.1. Company Overview11.9.2. Financial Performance11.9.3. Product Benchmarking11.9.4. Recent Development11.10. The Swatch Group AG11.10.1. Company Overview11.10.2. Financial Performance11.10.3. Product Benchmarking11.10.4. Recent Development

For more information about this report visit https://www.researchandmarkets.com/r/61onfk

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The Worldwide Jewelry Industry is Expected to Reach $459 Billion by 2030 - GlobeNewswire

Data Science and Machine-Learning Platforms Market Key Segments to Play Solid Role In A Booming Industry| Databricks, TIBCO Software, MathWorks The…

May 23, 2022 | Author: admin

Latest Study on Industrial Growth of Global Data Science and Machine-Learning Platforms Market 2021-2027. A detailed study accumulated to offer Latest insights about acute features of the Data Science and Machine-Learning Platforms market. The report contains different market predictions related to revenue size, production, CAGR, Consumption, gross margin, price, and other substantial factors. While emphasizing the key driving and restraining forces for this market, the report also offers a complete study of the future trends and developments of the market. It also examines the role of the leading market players involved in the industry including their corporate overview, financial summary and SWOT analysis.

The Major Players Covered in this Report: SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks, TIBCO Software, MathWorks, H20.ai, Anaconda, SAP, Google, Domino Data Lab, Angoss, Lexalytics, Rapid Insight & ?Data Science and Machine-Learning PlatformsMarket Scope and Market Breakdown

Data Science and Machine-Learning Platforms Market Study guarantees you to remain / stay advised higher than your competition. With Structured tables and figures examining the Data Science and Machine-Learning Platforms, the research document provides you a leading product, submarkets, revenue size and forecast to 2027. Comparatively is also classifies emerging as well as leaders in the industry.Click To get SAMPLE PDF of Data Science and Machine-Learning Platforms Market (Including Full TOC, Table & Figures) @https://www.htfmarketreport.com/sample-report/4053689-global-data-science-and-machine-learning-platforms-market-7

This study also covers company profiling, specifications and product picture, sales, market share and contact information of various regional, international and local vendors of Global Data Science and Machine-Learning Platforms Market. The market proposition is frequently developing ahead with the rise in scientific innovation and M&A activities in the industry. Additionally, many local and regional vendors are offering specific application products for varied end-users. The new merchant applicants in the market are finding it hard to compete with the international vendors based on reliability, quality and modernism in technology.

Read Detailed Index of full Research Study at @https://www.htfmarketreport.com/reports/4053689-global-data-science-and-machine-learning-platforms-market-7

The titled segments and sub-section of the market are illuminated below:In-depth analysis of Global Data Science and Machine-Learning Platforms market segments by Types: , Open Source Data Integration Tools & Cloud-based Data Integration ToolsDetailed analysis of Global Data Science and Machine-Learning Platforms market segments by Applications: on, Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises, Channel, By Channels, Market has been segmented into, Direct Sales, Distribution Channel, Regional & Country Analysis, North America Country (United States, Canada), South America (Brazil, Argentina, Peru, Chile, Rest of South America), Asia-Pacific (China, Japan, India, South Korea, Australia, Singapore, Malaysia, Indonesia, Philippines, Thailand, Vietnam, Others), Europe (Germany, United Kingdom, France, Italy, Spain, Switzerland, Netherlands, Austria, Sweden, Norway, Belgium, Rest of Europe) & Rest of World [United Arab Emirates, Saudi Arabia (KSA), South Africa, Egypt, Turkey, Israel, Others]

Major Key Players of the Market:SAS, Alteryx, IBM, RapidMiner, KNIME, Microsoft, Dataiku, Databricks, TIBCO Software, MathWorks, H20.ai, Anaconda, SAP, Google, Domino Data Lab, Angoss, Lexalytics, Rapid Insight & ?Data Science and Machine-Learning PlatformsMarket Scope and Market Breakdown

Regional Analysis for Global Data Science and Machine-Learning Platforms Market: APAC (Japan, China, South Korea, Australia, India, and Rest of APAC; Rest of APAC is further segmented into Malaysia, Singapore, Indonesia, Thailand, New Zealand, Vietnam, and Sri Lanka) Europe (Germany, UK, France, Spain, Italy, Russia, Rest of Europe; Rest of Europe is further segmented into Belgium, Denmark, Austria, Norway, Sweden, The Netherlands, Poland, Czech Republic, Slovakia, Hungary, and Romania) North America (U.S., Canada, and Mexico) South America (Brazil, Chile, Argentina, Rest of South America) MEA (Saudi Arabia, UAE, South Africa)

Furthermore, the years considered for the study are as follows:Historical year 2015-2020Base year 2020Forecast period** 2021 to 2027 [** unless otherwise stated]

**Moreover, it will also include the opportunities available in micro markets for stakeholders to invest, detailed analysis of competitive landscape and product services of key players.

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Key takeaways from the Global Data Science and Machine-Learning Platforms market report: Detailed considerate of Data Science and Machine-Learning Platforms market-particular drivers, Trends, constraints, Restraints, Opportunities and major micro markets. Comprehensive valuation of all prospects and threat in the In depth study of industry strategies for growth of the Data Science and Machine-Learning Platforms market-leading players. Data Science and Machine-Learning Platforms market latest innovations and major procedures. Favorable dip inside Vigorous high-tech and market latest trends remarkable the Market. Conclusive study about the growth conspiracy of Data Science and Machine-Learning Platforms market for forthcoming years.

What to Expect from this Report On Data Science and Machine-Learning Platforms Market:1. A comprehensive summary of several area distributions and the summary types of popular products in the Data Science and Machine-Learning Platforms Market.2. You can fix up the growing databases for your industry when you have info on the cost of the production, cost of the products, and cost of the production for the next future years.3. Thorough Evaluation the break-in for new companies who want to enter the Data Science and Machine-Learning Platforms Market.4. Exactly how do the most important companies and mid-level companies make income within the Market?5. Complete research on the overall development within the Data Science and Machine-Learning Platforms Market that helps you elect the product launch and overhaul growths.

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Detailed TOC of Data Science and Machine-Learning Platforms Market Research Report-

Data Science and Machine-Learning Platforms Introduction and Market Overview Data Science and Machine-Learning Platforms Market, by Application [on, Small-Sized Enterprises, Medium-Sized Enterprise, Large Enterprises, Channel, By Channels, Market has been segmented into, Direct Sales, Distribution Channel, Regional & Country Analysis, North America Country (United States, Canada), South America (Brazil, Argentina, Peru, Chile, Rest of South America), Asia-Pacific (China, Japan, India, South Korea, Australia, Singapore, Malaysia, Indonesia, Philippines, Thailand, Vietnam, Others), Europe (Germany, United Kingdom, France, Italy, Spain, Switzerland, Netherlands, Austria, Sweden, Norway, Belgium, Rest of Europe) & Rest of World [United Arab Emirates, Saudi Arabia (KSA), South Africa, Egypt, Turkey, Israel, Others]] Data Science and Machine-Learning Platforms Industry Chain Analysis Data Science and Machine-Learning Platforms Market, by Type [, Open Source Data Integration Tools & Cloud-based Data Integration Tools] Industry Manufacture, Consumption, Export, Import by Regions (2015-2020) Industry Value ($) by Region (2015-2020) Data Science and Machine-Learning Platforms Market Status and SWOT Analysis by Regions Major Region of Data Science and Machine-Learning Platforms Marketi) Global Data Science and Machine-Learning Platforms Salesii) Global Data Science and Machine-Learning Platforms Revenue & market share Major Companies List Conclusion

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, MINT, BRICS, G7, Western / Eastern Europe or Southeast Asia. Also, we can serve you with customize research services as HTF MI holds a database repository that includes public organizations and Millions of Privately held companies with expertise across various Industry domains.

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Data Science and Machine-Learning Platforms Market Key Segments to Play Solid Role In A Booming Industry| Databricks, TIBCO Software, MathWorks The...

Building the connected utility of the future – Utility Dive

May 23, 2022 | Author: admin

Todays utilities bear little resemblance to the utility companies from decades ago.

For most of the last century, electric utilities operations were built around an architecture of one-directional flow of power from generation to customers, under fairly predictable conditions. Now, however, the environment in which utilities operate looks far different.

Climate change is contributing to wildfires and temperature extremes, forcing many utility companies to run in conditions they never planned for.1At the same time, the integration of renewable generation, storage and other DERs is driving a shift to a DSO model in which the grid is more distributed and electricity flows bidirectionally between utilities and consumers. Finally, through consolidations and mergers, utilities have grown more organizationally complex, adding yet another hurdle to dynamically responding to these new conditions.

Addressing the breadth of these challenges requires an unprecedented level of connectivity across distributed organizations. To harden systems, predict when equipment will fail and communicate thoughtfully with tens of thousands of customers during emergency events, utilities need an enterprise-wide data-driven operating system that spans across operators, analysts and leaders.

Utilities today have access to a rich set of data, but they may not be leveraging it to its fullest extent. With the right systems in place, utilities can gather real-time signal about grid operations from smart meters, leverage LiDAR to achieve highly accurate GIS records and deploy drones to remotely inspect asset conditions. To harness this data, many utilities are investing in data science teams and new ML/AI off-the-shelf toolkits. While these efforts frequently create impressive data assets and promising models, many prototypes fail to make it to production and actually achieve the promised operational improvements.

For example, imagine a utility that has begun a pilot project to deploy new sensors to help manage DER integration. The data science team has leveraged industry-standard data science tools to detect power quality faults and recommend where maintenance inspections should begin looking to find the source of the problem.

To get this off the ground, each day, the data science teams business counterparts export spreadsheets of model outputs for maintenance engineers.

Engineers then review recommendations in conjunction with context from other applications a time-consuming and error-prone process before committing decisions to a legacy scheduling system. As part of the review, engineers cross-check the modeling outputs with various maintenance schedules, often performing ad-hoc analysis based on their real-world experience. Moreover, stale historical assumptions are often baked into these models, requiring the engineers to manually correct the same discrepancies every time the data science team delivers a fresh set of outputs.

For the data science team, developing models is also a manual and painful process, involving manual data cleaning and feature engineering. The data scientists struggle to run the model across all feeders and to leverage models from other analytic projects. Most crucially, they dont get timely feedback from their consumers. Without frequent updates on which recommendations were accurate and which werent, it proves difficult to iteratively improve the models over time and ensure that they were accurate.

With so many distributed sources of information and the messy process of combining human insights with data, utilities may find it challenging to make the most of their investments in new data sources and analytical capabilities. Many utility companies may face technical and organizational barriers that prevent their data, analytics, engineering and operational teams from iterating closely together.

For decades, utilities have relied on foundational software systems that are critical to the electric power infrastructure, but also highly constraining. Purpose-built on-premises systems like DMS, SCADA and GIS are foundational for managing grid infrastructure data, but theyre specialized for a narrow set of data and operational processes, making them of limited use for utilities grappling with an ever-evolving set of challenges.

Newer iterations on these systems, like ADMS and DERMS, promise to help utilities manage a more distributed, DER-friendly grid. However, they are still too specialized to deal with the larger issues facing utilities. These systems don't typically integrate external data, leverage custom models, or help utility companies build new workflows. Utilities will need these capabilities and more, to adapt their operations in the face of two-way power flow across distributed energy resources, more complex weather events, and other challenges of the twenty-first century.

Outside of these systems, utilities have followed the lead of other industries in investing in new cloud systems like data warehouses and analytics engines. These perform capably at collecting data from different sources, but they are removed from the core operations that made the legacy systems, like DMS and EMS, so valuable. Cloud-based data warehouses may summarize a complex reality, but they dont offer levers to act or respond to new threats. They don't go the last mile of getting these analytics into the hands of field crews and grid operators so that they can make better decisions day after day. For instance, even after years of investment in cloud modernization, when faced with an emergency operation or urgent new work program, many utilities rely heavily on spreadsheets, emails and file shares, which quickly become outdated and don't leave a trail of where information came from. Often, the newer cloud tools don't actually improve the operational bottom line when they're needed most.

In the face of massive disruption, analytics alone arent enough: utilities need a platform that can help them power complex operations by combining the best of data and human insight. This platform should break down data silos and ultimately enable a feedback loop between data teams, analysts, engineering and planning teams and grid operators.

Pacific Gas and Electric (PG&E) uses Palantir Foundry to layer together different sets of information, such as real-time grid conditions and risk models. The utility can also conduct preventive maintenance by developing models to predict equipment health, analyzing smart meter data to understand where to prioritize repairs. PG&E credits Foundry with helping the company manage the risk of wildfires caused by electrical equipment, ultimately keeping Californians safer.

Palantir has partnered with many utilities to deploy Foundry across the value chain, from emergency operations to predictive maintenance to EV planning. To learn more about how Foundry can help your utilitys decision-making capabilities, check out our website and meet us at DISTRIBUTECH in Dallas, TX from May 23-25.

1) Jones, Matthew W., Adam Smith, Richard Betts, Josep G. Canadell, I. Colin Prentice, and Corinne Le Qur. "Climate change increases the risk of wildfires." ScienceBrief Review 116 (2020): 117. https://www.preventionweb.net/files/73797_wildfiresbriefingnote.pdf

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Building the connected utility of the future - Utility Dive

Consumer anaytics and data science – Times of India

May 23, 2022 | Author: admin

Consumer Analytics is the area in which the consumer data can be extracted to get the maximum insights. The data is being received from different sources viz. digital media and the other media. The touch points in the organization provide the immense data and the same can be analyzed by the marketers for their maximum benefit.

The changing trends in the market are driving the companies to work on the unused data which is derived from the customer feedbacks. It is the processes that defines the customer satisfaction on various products. The inputs adopted by the marketers can lead to storage of data in the cloud form in the organizations.

The data mining tools enable the useful data to be exploited out of the total data available in the warehouses. The virtual space has the potential of bringing the data which is analyzed by the marketers for their deciions in the businesses. The consumer behaviour is visible through the data retrieved by the marketers.

The use of data science is making the consumer analytics strong as the extent of visualization becomes effective. The emerging tools in data science may augment the usage of consumer analytics. The key to successful organization lies in the triangulation of Consumer analytics, data science and technology.

Views expressed above are the author's own.

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Consumer anaytics and data science - Times of India

Informatica World 2022 Showcases Global Customer Adoption of the Intelligent Data Management Cloud (IDMC) – Yahoo Finance

May 23, 2022 | Author: admin

Customers Volvo, Pepsi, ADT, Telus and FreddieMac to share Cloud Modernization success with IDMC at Informatica's annual customer conference

Informatica deepens partnerships with AWS, Microsoft, Google Cloud, Snowflake and Databricks to accelerate cloud migrations with IDMC

IDMC powered by Informatica's AI engine, CLAIRE processes 32 trillion transactions per month on the cloud

REDWOOD CITY, Calif., May 23, 2022 /PRNewswire/ --Informatica(NYSE:INFA), an enterprise cloud data management leader will be kicking off its annual customer conference, Informatica Worldas a hybrid event in Las Vegas today with over 60-plus global customers presenting how the Informatica Intelligent Data Management Cloud(IDMC) has accelerated their cloud journeys and driven better business outcomes.

Informatica Corp. (PRNewsfoto/Informatica Corp.)

IDMC was launched at Informatica World 2021 as the industry's first end-to-end data management platform designed to help businesses truly innovate with their data on any system, any cloud, multi-cloud and multi-hybrid and for all users across the enterprise. IDMC is a comprehensive, AI-powered, cloud data management platform offering over 200-plus intelligent cloud services to help organizations reimagine and redefine how they can innovate business functions from customer experience, e-commerce, supply chain, manufacturing to analytics and data science, with a mission to create a world where every organization's data is poised for greatness and empowered to deliver outcomes.

Since its launch last year, IDMC has been recognized as a leader in iPaaS, 2021's best new product of the year by the Business Intelligence group and also recognized in Fast Company's most innovative list in the enterprise category. Informatica's cloud annual recurring revenue has grown 43% year-over-year as of March 31, 2022 with global customers across a wide variety of industry verticals investing in the IDMC platform. CLAIRE, Informatica's AI engine powers the IDMC platform to process over 32 trillion transactions (as of March 31, 2022) on the cloud each month and that number is doubling every six to 12 months.

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At Informatica World this week, the company will be unveiling new industry-verticalized capabilities for IDMC to help customers in the financial services, healthcare and life sciences address industry-specific data management and governance needs. With over $1Billion in investments in R&D over the last six years, Informatica has designed and delivered an iPaaS cloud platform that is helping customers like Pepsi, Volvo, ADT, Telus, FreddieMac, Blue Cross Blue Shield of Kansas City and Hershey, modernize to the cloud with IDMC. Over 3,000 attendees joining the hybrid event will hear from these customers at Informatica World on how IDMC is helping with their data-led business transformation.

Informatica's rich ecosystem of partners which include all the major hyperscalers, AWS, Microsoft, Google Cloud, Snowflake, Databricks as well as GSI partners like Accenture, Deloitte, CapGemini, Wipro and Infoverity has deep integrations with the IDMC platform to bring best-of-breed cloud data management solutions to joint customers. The company will be announcing deeper product integrations with major hyperscalers this week at Informatica World and will also be featuring Scott Guthrie, SVP, Cloud +AI Group, Microsoft; Thomas Kurian, CEO, Google Cloud; Matt Garman, SVP, Sales, Marketing and Global Sales at AWS as keynote speakers.

"When we embarked on the company's transformation six years agao, we completely rearchitected our entire product portfolio to be cloud-first, cloud-native,"said Amit Walia, CEO, Informatica. "Today with IDMC, we bring an unparalleled cloud data management platform that is helping our customers build an intelligent data enterprise to stay competitive in a digital-first economy. I am very excited to see the fantastic lineup of speakers including our customers across multiple industries and our global partners talking about how they are driving business value and transforming how they run their business with IDMC, at Informatica World."

Join Informatica World virtually to listen to cloud and data industry leaders and visionaries at http://www.informaticaworld.com

About InformaticaInformatica (NYSE: INFA), an Enterprise Cloud Data Management leader, empowers businesses to realize the transformative power of data. We have pioneered a new category of software, the Informatica Intelligent Data Management Cloud(IDMC), powered by AI and a cloud-first, cloud-native, end-to-end data management platform that connects, manages, and unifies data across any multi-cloud, hybrid system, empowering enterprises to modernize and advance their data strategies. Over 5,000 customers in more than 100 countries and 85 of the Fortune 100 rely on Informatica to drive data-led digital transformation.

Contact: Informatica Public Relationsprteam@informatica.com

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Informatica World 2022 Showcases Global Customer Adoption of the Intelligent Data Management Cloud (IDMC) - Yahoo Finance

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