Blockchain Platforms Software Market Size and Forecast (2020-2027) | By Top Leading Players …

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    To understand Blockchain Platforms Software market dynamics, the market is analyzed in key regions and countries around the world. Market Research Intellect offers tailor-made specific regional and country-specific analyzes of the most important regions as follows:

    North America: USA, Canada, Mexico

    Latin America: Argentina, Chile, Brazil, Peru and the rest of Latin America

    Europe: UK, Germany, Spain, Italy and the rest of the EU

    Asia Pacific: India, China, Japan, South Korea, Australia, and the rest of APAC

    Middle East and Africa: Saudi Arabia, South Africa, United Arab Emirates and the rest of the MEA

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    Key elements of the report:

    Market scenario:

    The report highlights the key features of the trading area of ​​the Blockchain Platforms Software industry. It covers development trends, market growth factors, and segments that affect market growth. It covers the types of products, applications, types, deployments, and developments in the market.

    Market highlights:

    The report provides an in-depth market analysis with key elements, sales estimates, cost analysis, import / export, production and consumption trends, CAGR, gross margin as well as supply samples and upon request. The report also provides an overview of development factors and models of progress in the Blockchain Platforms Software industry.

    Analysis tools:

    The Blockchain Platforms Software market is assessed through extensive primary and secondary research, which is then validated and verified by industry experts and professionals. The report studies the major market players along with their market position, share, revenue, gross margin, and business strategies. Porter’s SWOT Analysis and Five Forces Analysis are conducted to study and evaluate the market and its players. Additionally, the report provides a feasibility study and ROI analysis to help readers develop strategic investment plans.

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    About Us:

    Market Research Intellect provides syndicated and customized research reports to clients from various industries and organizations with the aim of delivering functional expertise. We provide reports for all industries including Energy, Technology, Manufacturing and Construction, Chemicals and Materials, Food and Beverage, and more. These reports deliver an in-depth study of the market with industry analysis, the market value for regions and countries, and trends that are pertinent to the industry.

    Contact Us:

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    Market Research Intellect

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    Impact Of Outbreak Of Coronavirus (Covid-19) On Blockchain Platforms Software Market 2020 …

    Global Blockchain Platforms Software Market 2020-2026 – Global Industry Size, Supply Analysis, Price Analysis, Consumption and Production, Supplier and Cost Structure Analysis

    The Blockchain Platforms Software market research report added by Market Data Analytics is an in-depth analysis of the latest developments, market dynamics, status, approaching technologies, industry drivers, market defies, regulatory policies, and the key market players and their strategies. The Blockchain Platforms Software research study offers market introduction, definition, regional market trends, regional trades and revenue, production cost analysis, supply & demand chain, and market size forecast. The research report defines the market data in a tabular, pie chart, graphical and figurative format from the perspective of business intelligence.

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    Final Report will add the analysis of the impact of COVID-19 on this Industry.

    The report encompasses the present and forecast analysis in order to gain a better understanding of the market status on the global platform. Additionally, the competition landscape necessitating share analysis of the major company players in the Blockchain Platforms Software market based on their economic and other substantial factors are also mentioned in the report. Along with the developments made by the prominent players in the Blockchain Platforms Software market even the complete overview of growth analysis together with historical & futuristic costs is provided as beneficial source in the report. There is also certain detailing related to supply data, company profile, and revenue mentioned.

    Competitive Landscape of Blockchain Platforms Software market:

    Majority of the key players of the Blockchain Platforms Software market are mentioned in the report. This section is projected to help the readers gain knowledge over the collaborations and strategies used by players in the market. The global revenue and sales of manufacturers provides a microscopic look at the market and also the footprints of the key players IBM, Intel, Microsoft, Ethereum, Ripple, Quorum, Hyperledger, R3 Corda, EOS, OpenChain, Stellar, SAP, Amazon, Mastercard.

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    Segmentation Analysis of Blockchain Platforms Software market:

    The comprehensive report includes segments by regions, company, and other segments. The regional segmentation North America (United States, Canada and Mexico), Europe (Germany, France, United Kingdom, Russia and Italy), Asia-Pacific (China, Japan, Korea, India, Southeast Asia and Australia), Latin America (Brazil, Argentina), and the Middle East & Africa (Saudi Arabia, UAE, Egypt and South Africa) helps identifying the importance of various factors that aid market growth and development. Further, the other segments {Private, Public, Consortium}; {E-Commerce, Finance, Medicine, Real Estate} provide details related to the sales and revenue from the present to the future. The report has been curated after thorough observation and analysis of various factors such as economic, technological, environmental, social, and political status.

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    Reasons to purchase this report:

    • The report provides a complete analysis of country lever, regional, and global markets

    • Analysis of the historical information coupled with the present and future market trends

    • Key market strategy initiatives of the major players in the Blockchain Platforms Software market

    • In-depth study of the impact of frequently altering global market developments on the market

    Why Go For Market Data Analytics Research?

    Market Data Analytics is a leading global market research and consulting firm. We focus on business consulting, industrial chain research, and consumer research to help customers provide non-linear revenue models. We believe that quality is the soul of the business and that is why we always strive for high quality products. Over the years, with our efforts and support from customers, we have collected inventive design methods in various high-quality market research and research teams with extensive experience.

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    The world collectively has been bracing for a change in the job landscape. Driven largely by the emergence of new technologies like data science and artificial intelligence (AI), these changes have already made some jobs redundant. To add to this uncertainty, the catastrophic economic impact of the Covid-19 pandemic has brought in an urgency to upskill oneself to adapt to changing scenarios.

    While the prognosis does not look good, this could also create the demand for jobs in the field of business analytics. This indicates that heavily investing in data science and AI skills today could mean the difference between you being employed or not tomorrow.

    By adding more skills to your arsenal today, you can build your core competencies in areas that will be relevant once these turbulent times pass over. This includes sharpening your understanding of business numbers and analysing consumer demands – two domains which businesses will heavily invest in very soon.



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    Analytics Edge (Data Visualization & Analytics)

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    Duration: While the original data analytics course this short-term course is developed from includes 180 hours of content and demands an average of 10-15 hours of weekly online classes and self-study. This course will enable you to acquire the same skills, but within a shorter period of time.

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    About the course: Adapted to greatly help candidates when searching for data science roles, this certification covers all that they need to know on the subject using Python as the programming language. While other languages like R are also commonly used today, Python has emerged as one of the more popular options within the data science universe.

    This ‘Python for Data Science’ course will make you proficient in defly handling and visualizing data, and also covers statistical modelling and operations with NumPy. It also integrates these with practical examples and case studies, making it a unique online training data science course in Python.

    Duration of the course: While the original data science course this short-term course is developed from includes 220 hours of content and demands an average of 15-20 hours of weekly online classes and self-study, this course will enable you to acquire the same skills, but within a shorter period of time.

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    Thus, after successful completion of this Applied AI course, you will not only be proficient in the theoretical aspects of AI and ML, but will also develop a nuanced understanding of its industry applications.

    Duration of the course: While the original ML and AI course this short-term course is developed from includes 280 hours of content and demands an average of 8-10 hours of weekly self-study, this Applied AI course will enable you to acquire the same skills, but within a shorter period of time.

    Target Group: While anyone with an interest in analytics can pursue this course, it is especially targeted at candidates with a background in engineering, finance, math, statistics, and business management. It will also help people who want to acquire AI and machine learning skills to head start their career in the field of data science.

    Summary

    While the Covid-19 pandemic has witnessed a partial – or even complete – lockdown at several places across the globe, people have been reorienting their lives indoors. But with no end in sight, it necessitates that professionals turn these circumstances into opportunities to upskill.

    Given an oncoming recession and economic downturn, it behoves them to adapt to these changes to remain employable in such competitive times. In this setting, Covid-19 could emerge as a tipping point for learning, with virtual learning offering the perfect opportunity to self-learn.

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    Related:

    COVID-19 Impact: Temporary Surge in Sales of Big Data Analytics in Automotive Product Observed …

    Big Data Analytics in Automotive Market 2018: Global Industry Insights by Global Players, Regional Segmentation, Growth, Applications, Major Drivers, Value and Foreseen till 2024

    The report provides both quantitative and qualitative information of global Big Data Analytics in Automotive market for period of 2018 to 2025. As per the analysis provided in the report, the global market of Big Data Analytics in Automotive is estimated to growth at a CAGR of _% during the forecast period 2018 to 2025 and is expected to rise to USD _ million/billion by the end of year 2025. In the year 2016, the global Big Data Analytics in Automotive market was valued at USD _ million/billion.

    This research report based on ‘ Big Data Analytics in Automotive market’ and available with Market Study Report includes latest and upcoming industry trends in addition to the global spectrum of the ‘ Big Data Analytics in Automotive market’ that includes numerous regions. Likewise, the report also expands on intricate details pertaining to contributions by key players, demand and supply analysis as well as market share growth of the Big Data Analytics in Automotive industry.

    Get Free Sample PDF (including COVID19 Impact Analysis, full TOC, Tables and Figures) of Market Report @ https://www.researchmoz.com/enquiry.php?type=S&repid=2636782&source=atm

    Big Data Analytics in Automotive Market Overview:

    The Research projects that the Big Data Analytics in Automotive market size will grow from in 2018 to by 2024, at an estimated CAGR of XX%. The base year considered for the study is 2018, and the market size is projected from 2018 to 2024.

    The report on the Big Data Analytics in Automotive market provides a bird’s eye view of the current proceeding within the Big Data Analytics in Automotive market. Further, the report also takes into account the impact of the novel COVID-19 pandemic on the Big Data Analytics in Automotive market and offers a clear assessment of the projected market fluctuations during the forecast period. The different factors that are likely to impact the overall dynamics of the Big Data Analytics in Automotive market over the forecast period (2019-2029) including the current trends, growth opportunities, restraining factors, and more are discussed in detail in the market study.

    Leading manufacturers of Big Data Analytics in Automotive Market:

    The key players covered in this study

    Advanced Micro Devices

    Big Cloud Analytics

    BMC Software

    Cisco Systems

    Deloitte

    Fractal Analytics

    IBM Corporation

    Rackspace

    Red Hat

    SmartDrive Systems

    Market segment by Type, the product can be split into

    Hardware

    Software

    Services

    Managed

    Professional

    Market segment by Application, split into

    Product Development

    Manufacturing & Supply Chain

    After-Sales, Warranty & Dealer Management

    Connected Vehicles & Intelligent Transportation

    Marketing, Sales & Other Applications

    Market segment by Regions/Countries, this report covers

    North America

    Europe

    China

    Japan

    Southeast Asia

    India

    Central & South America

    The study objectives of this report are:

    To analyze global Big Data Analytics in Automotive status, future forecast, growth opportunity, key market and key players.

    To present the Big Data Analytics in Automotive development in North America, Europe, China, Japan, Southeast Asia, India and Central & South America.

    To strategically profile the key players and comprehensively analyze their development plan and strategies.

    To define, describe and forecast the market by type, market and key regions.

    In this study, the years considered to estimate the market size of Big Data Analytics in Automotive are as follows:

    History Year: 2015-2019

    Base Year: 2019

    Estimated Year: 2020

    Forecast Year 2020 to 2026

    For the data information by region, company, type and application, 2019 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.

    Do You Have Any Query Or Specific Requirement? Ask to Our Industry [email protected]https://www.researchmoz.com/enquiry.php?type=E&repid=2636782&source=atm

    Some important highlights from the report include:

    • The report offers a precise analysis of the product range of the Big Data Analytics in Automotive market, meticulously segmented into applications
    • Key details concerning production volume and price trends have been provided.
    • The report also covers the market share accumulated by each product in the Big Data Analytics in Automotive market, along with production growth.
    • The report provides a brief summary of the Big Data Analytics in Automotive application spectrum that is mainly segmented into Industrial Applications
    • Extensive details pertaining to the market share garnered by each application, as well as the details of the estimated growth rate and product consumption to be accounted for by each application have been provided.
    • The report also covers the industry concentration rate with reference to raw materials.
    • The relevant price and sales in the Big Data Analytics in Automotive market together with the foreseeable growth trends for the Big Data Analytics in Automotive market is included in the report.
    • The study offers a thorough evaluation of the marketing strategy portfolio, comprising several marketing channels which manufacturers deploy to endorse their products.
    • The report also suggests considerable data with reference to the marketing channel development trends and market position. Concerning market position, the report reflects on aspects such as branding, target clientele and pricing strategies.
    • The numerous distributors who belong to the major suppliers, supply chain and the ever-changing price patterns of raw material have been highlighted in the report.
    • An idea of the manufacturing cost along with a detailed mention of the labor costs is included in the report.

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    The Questions Answered by Big Data Analytics in Automotive Market Report:

    • What are the Key Manufacturers, raw material suppliers, equipment suppliers, end users, traders And distributors in Big Data Analytics in Automotive Market ?
    • What are Growth factors influencing Big Data Analytics in Automotive Market Growth?
    • What are production processes, major issues, and solutions to mitigate the development risk?
    • What is the Contribution from Regional Manufacturers?
    • What are the Key Market segment, market potential, influential trends, and the challenges that the market is facing?

    And Many More….

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    Blockchain Platforms Software Market Forecasts (2020-2024) with Industry Chain Structure …

    Global Blockchain Platforms Software Market This research report provides detailed study accumulated to offer Latest insights about acute features of the Blockchain Platforms Software Market. The report contains different market predictions related to market size, revenue, 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. It presents the 360-degree overview of the competitive landscape of the industries. Blockchain Platforms Software Market is showing steady growth and CAGR is expected to improve during the forecast period.

    Click Here to Get Free PDF Sample Copy of this Report!

    Manufacturer Detail

    IBM

    Intel

    Microsoft

    Ethereum

    Ripple

    Quorum

    Hyperledger

    R3 Corda

    EOS

    OpenChain

    Stellar

    SAP

    Amazon

    Mastercard

    Product Type Segmentation

    Private

    Public

    Consortium

    Industry Segmentation

    E-Commerce

    Finance

    Medicine

    Real Estate

    Global Blockchain Platforms Software Market report provides you with detailed insights, industry knowledge, market forecasts and analytics. The report on the global Blockchain Platforms Software industry also clarifies economic risks and environmental compliance. Global Blockchain Platforms Software market report assists industry enthusiasts including investors and decision makers to make confident capital investments, develop strategies, optimize their business portfolio, innovate successfully and perform safely and sustainably.

    Do You Have Any Query? Ask to Our Industry Expert!

    Blockchain Platforms Software Market: Regional Analysis Includes:

    • Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
    • Europe (Turkey, Germany, Russia UK, Italy, France, etc.)
    • North America (the United States, Mexico, and Canada.)
    • South America (Brazil etc.)
    • The Middle East and Africa (GCC Countries and Egypt.)

    Major Points Covered in TOC:

    • Overview: Along with a broad overview of the global Blockchain Platforms Software Market, this section gives an overview of the report to give an idea about the nature and contents of the research study.
    • Analysis on Strategies of Leading Players: Market players can use this analysis to gain competitive advantage over their competitors in the Blockchain Platforms Software Market.
    • Study on Key Market Trends: This section of the report offers deeper analysis of latest and future trends of the market.
    • Market Forecasts: Buyers of the report will have access to accurate and validated estimates of the total market size in terms of value and volume. The report also provides consumption, production, sales, and other forecasts for the Blockchain Platforms Software Market.
    • Regional Growth Analysis: All major regions and countries have been covered Blockchain Platforms Software Market report. The regional analysis will help market players to tap into unexplored regional markets, prepare specific strategies for target regions, and compare the growth of all regional markets.
    • Segment Analysis: The report provides accurate and reliable forecasts of the market share of important segments of the Blockchain Platforms Software Market. Market participants can use this analysis to make strategic investments in key growth pockets of the Blockchain Platforms Software Market.

    Key Questions Answered in the Report Include:

    • What will the market size and the growth rate be in 2025?
    • What are the key factors driving the global Blockchain Platforms Software Market?
    • What are the key market trends impacting the growth of the global Blockchain Platforms Software Market?
    • What are the challenges to market growth?
    • Who are the key vendors in the global Blockchain Platforms Software Market?
    • What are the market opportunities and threats faced by the vendors in the global Blockchain Platforms Software Market?
    • Trending factors influencing the market shares of the Americas, APAC, Europe, and MEA.
    • What are the key outcomes of the five forces analysis of the global Blockchain Platforms Software Market?

    Directly Purchase This Research Report Now!

    A free report data (as a form of Excel Datasheet) will also be provided upon request along with a new purchase.

    Note – In order to provide more accurate market forecast, all our reports will be updated before delivery by considering the impact of COVID-19.

    About Us:

    Qurate Business Intelligence delivers unique market research solutions to its customers and help them to get equipped with refined information and market insights derived from reports. We are committed to providing best business services and easy processes to get the same. Qurate Business Intelligence considers themselves as strategic partners of their customers and always shows the keen level of interest to deliver quality.

    Contact Us :

    Web: www.qurateresearch.com

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    Ph: US – +13393375221, IN – +919881074592

    Qurate Business Intelligence
    Qurate Business Intelligence delivers unique Market research solutions to its customers and help them to get equipped with refined information and Market insights derived from reports. We are committed to providing best business services and easy processes to get the same. Qurate Business Intelligence considers themselves as strategic partners of their customers and always shows the keen level of interest to deliver quality.
    Qurate Business Intelligence

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    Four Tools to Integrate into Your Data Lake

    A data lake is an absolutely vital piece of today’s big data business environment. A single company may have incoming data from a huge variety of sources, and having a means to handle all of that is essential. For example, your business might be compiling data from places as diverse as your social media feed, your app’s metrics, your internal HR tracking, your website analytics, and your marketing campaigns. A data lake can help you get your arms around all of that, funneling those sources into a single consolidated repository of raw data.

    But what can you do with that data once it’s all been brought into a data lake? The truth is that putting everything into a large repository is only part of the equation. While it’s possible to pull data from there for further analysis, a data lake without any integrated tools remains functional but cumbersome, even clunky.

    On the other hand, when a data lake integrates with the right tools, the entire user experience opens up. The result is streamlined access to data while minimizing errors during export and ingestion. In fact, integrated tools do more than just make things faster and easier. By expediting automation, the door opens to exciting new insights, allowing for new perspectives and new discoveries that can maximize the potential of your business.

    To get there, you’ll need to put the right pieces in place. Here are four essential tools to integrate into your data lake experience.

    Never miss an update about big data! Subscribe to the Big Data Blog to receive the latest posts straight to your inbox!

    Machine Learning

    Even if your data sources are vetted, secured, and organized, the sheer volume of data makes it unruly. As a data lake tends to be a repository for raw data—which includes unstructured items such as MP3 files, video files, and emails, in addition to structured items such as form data—much of the incoming data across various sources can only be natively organized so far. While it can be easy to set up a known data source for, say, form data into a repository dedicated to the fields related to that format, other data (such as images) arrives with limited discoverability.

    Machine learning can help accelerate the processing of this data. With machine learning, data is organized and made more accessible through various processes, including:

    In processed datasets, machine learning can use historical data and results to identify patterns and insights ahead of time, flagging them for further examination and analysis.

    With raw data, machine learning can analyze usage patterns and historical metadata assignments to begin implementing metadata automatically for faster discovery.

    The latter point requires the use of a data catalog tool, which leads us to the next point.

    Data Catalog

    Simply put, a data catalog is a tool that integrates into any data repository for metadata management and assignment. Products like Oracle Cloud Infrastructure Data Catalog are a critical element of data processing. With a data catalog, raw data can be assigned technical, operational, and business metadata. These are defined as:

    • Technical metadata: Used in the storage and structure of the data in a database or system
    • Business metadata: Contributed by users as annotations or business context
    • Operational metadata: Created from the processing and accessing of data, which indicates data freshness and data usage, and connects everything together in a meaningful way

    By implementing metadata, raw data can be made much more accessible. This accelerates organization, preparation, and discoverability for all users without any need to dig into the technical details of raw data within the data lake.

    Integrated Analytics

    A data lake acts as a middleman between data sources and tools, storing the data until it is called for by data scientists and business users. When analytics and other tools exist separate from the data lake, that adds further steps for additional preparation and formatting, exporting to CSV or other standardized formats, and then importing into the analytics platform. Sometimes, this also includes additional configuration once inside the analytics platform for usability. The cumulative effect of all these steps creates a drag on the overall analysis process, and while having all the data within the data lake is certainly a help, this lack of connectivity creates significant hurdles within a workflow.

    Thus, the ideal way to allow all users within an organization to swiftly access data is to use analytics tools that seamlessly integrate with your data lake. Doing so removes unnecessary manual steps for data preparation and ingestion. This really comes into play when experimenting with variability in datasets; rather than having to pull a new dataset every time you experiment with different variables, integrated tools allow this to be done in real time (or near-real time). Not only does this make things easier, this flexibility opens the door to new levels of insight as it allows for previously unavailable experimentation.

    Integrated Graph Analytics

    In recent years, data analysts have started to take advantage of graph analyticsthat is, a newer form of data analysis that creates insights based on relationships between data points. For those new to the concept, graph analytics considers individual data points similar to dots in a bubble—each data point is a dot, and graph analytics allows you to examine the relationship between data by identifying volume of related connections, proximity, strength of connection, and other factors.

    This is a powerful tool that can be used for new types of analysis in datasets with the need to examine relationships between data points. Graph analytics often works with a graph database itself or through a separate graph analytics tool. As with traditional analytics, any sort of extra data exporting/ingesting can slow down the process or create data inaccuracies depending on the level of manual involvement. To get the most out of your data lake, integrating cutting-edge tools such as graph analytics means giving data scientists the means to produce insights as they see fit.

    Why Oracle Big Data Service?

    Oracle Big Data Service is a powerful Hadoop-based data lake solution that delivers all of the needs and capabilities required in a big data world:

    • Integration: Oracle Big Data Service is built on Oracle Cloud Infrastructure and integrates seamlessly into related services and features such as Oracle Analytics Cloud and Oracle Cloud Infrastructure Data Catalog.
    • Comprehensive software stack: Oracle Big Data Service comes with key big data software: Oracle Machine Learning for Spark, Oracle Spatial Analysis, Oracle Graph Analysis, and much more.
    • Provisioning: Deploying a fully configured version of Cloudera Enterprise, Oracle Big Data Service easily configures and scales up as needed.
    • Secure and highly available: With built-in high availability and security measures, Oracle Big Data Service integrates and executes this in a single click.

    To learn more about Oracle Big Data Service, click here—and don’t forget to subscribe to the Oracle Big Data blog to get the latest posts sent to your inbox.

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    Blockchain Platforms Software Market to Witness Astonishing Growth by 2025 | IBM, Intel, Microsoft …

    Blockchain Platforms Software Market has recently added by Qurate Research to its vast repository. This intelligence report includes investigations based on Current scenarios, Historical records, and future predictions. An accurate data of various aspects such as Type, Size, Application, and end-user have been scrutinized in this research report. It presents the 360-degree overview of the competitive landscape of the industries. SWOT analysis has been used to understand the Strength, Weaknesses, Opportunities, and threats in front of the businesses. Thus, helping the companies to understand the threats and challenges in front of the businesses. Blockchain Platforms Software Market is showing steady growth and CAGR is expected to improve during the forecast period.

    Get a Free PDF Sample [email protected]

    Prominent Players Profiled in the Report are

    IBM

    Intel

    Microsoft

    Ethereum

    Ripple

    Quorum

    Hyperledger

    R3 Corda

    EOS

    OpenChain

    Stellar

    SAP

    Amazon

    Mastercard

    Product Type Segmentation

    Private

    Public

    Consortium

    Industry Segmentation

    E-Commerce

    Finance

    Medicine

    Real Estate

    The Blockchain Platforms Software market report includes comprehensive information about the market’s major competitors, including various organizations, companies, associations, suppliers and manufacturers competing for production, supply, sales, revenue generation, and after-sales performance expectations. The bargaining power of numerous vendors and buyers have also been included in the research report.

    Do You Have Any Query? Ask to Our Industry [email protected]

    Blockchain Platforms Software Market: Regional Analysis Includes:

    • Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
    • Europe (Turkey, Germany, Russia UK, Italy, France, etc.)
    • North America (the United States, Mexico, and Canada.)
    • South America (Brazil etc.)
    • The Middle East and Africa (GCC Countries and Egypt.)

    Key Question Answered in Report.

    • What are the strengths and weaknesses of the Blockchain Platforms Software Market?
    • What are the different marketing and distribution channels?
    • What is the current CAGR of the Blockchain Platforms Software Market?
    • What are the Blockchain Platforms Software market opportunities in front of the market?
    • What are the highest competitors in Blockchain Platforms Software market?
    • What are the key outcomes of SWOT and Porter’s five techniques?
    • What is the Blockchain Platforms Software market size and growth rate in the forecast period?

    Overview of the chapters analysing the global Blockchain Platforms Software Market in detail:

    • Chapter 1 details the information relating to Blockchain Platforms Software introduction, Scope of the product, market overview, Market risks, driving forces of the market, etc
    • Chapter 2 analyses the top manufacturers of the Blockchain Platforms Software Market by sales, revenue etc for the Forecast period 2020 to 2025
    • Chapter 3 analyze on the competition landscape amongst the top manufacturers based on sales, revenue, market share etc for the period 2020 to 2025.
    • Chapter 4 defines the global Blockchain Platforms Software market by regions and their market share, sales, revenue etc for the period 2020 to 2025.
    • Chapters 5 to 9 analyse the Blockchain Platforms Software regions with Blockchain Platforms Software countries based on market share, revenue, sales etc.
    • Chapter 10 and 11 contain the knowledge concerning market basis types and application, sales market share, growth rate etc for forecast period 2020 to 2025.
    • Chapter 12 focuses on the market forecast for 2020 to 2025 for the Blockchain Platforms Software Market by regions, type and application, sales and revenue.
    • Chapter 13 to 15 contain the transient details associate to sales channels, suppliers, traders, dealers, research findings and conclusion etc for the Blockchain Platforms Software Market.

    You Can Buy This Report From Here

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    What Is Oracle Cloud Infrastructure Data Catalog?

    And What Can You Do with It?

    Simply put, Oracle Cloud Infrastructure Data Catalog helps organizations manage their data by creating an organized inventory of data assets. It uses metadata to create a single, all-encompassing and searchable view to provide deeper visibility into your data assets across Oracle Cloud and beyond. This video provides a quick overview of the service.

    This helps data professionals such as analysts, data scientists, and data stewards discover and assess data for analytics and data science projects. It also supports data governance by helping users find, understand, and track their cloud data assets and on-premises data as well—and it’s included with your Oracle Cloud Infrastructure subscription.

    Never miss an update about big data! Subscribe to the Big Data Blog to receive the latest posts straight to your inbox!

    Why Does Oracle Cloud Infrastructure Data Catalog Matter?

    Hint: It has to do with self-service data discovery and governance.

    Oracle Cloud Infrastructure Data Catalog matters because it’s a foundational part of the modern data platform—a platform where all of your data stores can act as one, and you can view and access that data easily, no matter whether it resides in Oracle Cloud, object storage, an on-premises database, big data system, or a self-driving database.

    This means that data users—data scientists, data analysts, data engineers, and data stewards—can all find data across systems and the enterprise more easily because a data catalog provides a centralized, collaborative environment to encourage exploration. Now these key players can trust their data because they gain technical as well as business context around it. It means they don’t have to have SQL access, or understand what object storage is, or figure out the complexities of Hadoop—they can get started faster with their single unified view through their data catalog. It’s no longer necessary to have five different people with five different skillsets just to find where the right data resides.

    Easy data discovery is now possible.

    And of course, it’s not just data discovery that’s easier. Governance is also easier—and that is a key benefit with GDPR and ever more complex compliance requirements in today’s world of multiple enterprise systems, with on-premises, cloud, and multi-cloud environments.

    With Oracle Cloud Infrastructure Data Catalog, you have better visibility into all of your assets, and business context is available in the form of a business glossary and user annotations. And of course, understanding the data you have is essential for governance.

    How Does Oracle Cloud Infrastructure Data Catalog Work?

    Oracle Cloud Infrastructure Data Catalog takes metadata—technical, business, and operational—from various data sources, users, and assets, and harvests it to turn it into a data catalog: a single collaborative solution for data professionals to collect, organize, find, access, enrich, and activate metadata to support self-service data discovery and governance for trusted data assets across Oracle Cloud.

    And what’s so important about this metadata? Metadata is the key to Oracle Cloud Infrastructure Data Catalog. There are three types of metadata that are relevant and key to how our data catalog works:

    • Technical metadata: Used in the storage and structure of the data in a database or system
    • Business metadata: Contributed by users as annotations or business context
    • Operational metadata: Created from the processing and accessing of data, which indicates data freshness and data usage, and connects everything together in a meaningful way

    You can harvest this metadata from a variety of sources, including:

      • Oracle Cloud Infrastructure Object Storage
      • Oracle Database
      • Oracle Autonomous Transaction Processing
      • Oracle Autonomous Data Warehouse
      • Oracle MySQL Cloud Service
      • Hive
      • Kafka

    And the supported file types for Oracle Cloud Infrastructure Object Storage include:

      • CSV, Excel
      • ORC, Avro, Parquet
      • JSON

    Once the technical metadata is harvested, subject matter experts and data users can contribute business metadata in the form of annotations to the technical metadata. By organizing all this metadata and providing a holistic view into it, Oracle Cloud Infrastructure Data Catalog helps data users find the data they need, discover information on available data, and gain information about the trustworthiness of data for different uses.

    How Can You Use a Data Catalog?

    Metadata Enrichment

    Oracle Cloud Infrastructure Data Catalog enables users to collaboratively enrich technical information with business context to capture and share tribal knowledge. You can tag or link data entities and attributes to business terms to provide a more all-inclusive view as you begin to gather data assets for analysis and data science projects. These enrichments also help with classification, search, and data discovery.

    Business Glossaries

    One of the first steps towards effective data governance is establishing a common understanding of business concepts across the organization, and establishing their relationships to the data assets in the organization. Oracle Cloud Infrastructure Data Catalog makes it possible to see associations and linkages between glossary terms and other technical terms, assets, and artifacts. This helps increase user trust because users understand the relationships and what they’re looking at.

    Oracle Cloud Infrastructure Data Catalog makes this possible by including capabilities to collaboratively define business terms in rich text form, categorize them appropriately, and build a hierarchy to organize this vocabulary. You can also create parent-child relationships between various terms to build a taxonomy, or set business term owners and approval status so that users know who can answer their questions regarding specific terms. Once created, users can then link these terms to technical assets to provide business meaning and use them for searching as well.

    Searchable Data Asset Inventory

    By organizing all this metadata and providing a more complete view into it, Oracle Cloud Infrastructure Data Catalog helps users find the data they need, discover information on available data, and gain information about the trustworthiness of data for different uses.

    Being able to search across data stores makes finding the right data so much easier. With Oracle Cloud Infrastructure Data Catalog, you have a powerful, searchable, standardized inventory of the available data sources, entities, and attributes. You can enter technical information, defined tags, or business terms to easily pull up the right data entities and assets. You can also use filtering options to discover relevant datasets, or browse metadata based on the technical hierarchy of data assets, entities, and attributes. These features make it easier to get started with data science, analytics, and data engineering projects.

    Data Catalog API and SDK

    Many of Oracle Cloud Infrastructure Data Catalog’s capabilities are also available as public REST APIs to enable integrations such as:

    • Searching and displaying results in applications that use the data assets
    • Looking up definitions of defined business terms in the business glossary and displaying them in reporting applications
    • Invoking job execution to harvest metadata as needed

    Available search capabilities include:

    • Search data based on technical names, business terms, or tags
    • View details of various objects
    • Browse Oracle Cloud Infrastructure Data Catalog based on data assets

    Available single collaborative environment includes:

    • Homepage with helpful shortcuts and operational stats
    • Search and browse
    • Quick actions to manage data assets, glossaries, jobs, and schedules
    • Popular tags and recently updated objects

    Conclusion

    Oracle Cloud Infrastructure Data Catalog is the underlying foundation to data management that you’ve been waiting for—and it’s included with your Oracle Cloud Infrastructure subscription. Now, data professionals can use technical, business, and operational metadata to support self-service data discovery and governance for data assets in Oracle Cloud and beyond.

    Leverage your data in new ways, and more easily than you ever could before. Try Oracle Cloud Infrastructure Data Catalog today and start discovering the value of your data. And don’t forget to subscribe to the Big Data Blog for the latest on Big Data straight to your inbox!

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