Data Analytics Market Size, Share, Segmentation | Global Analysis by Type (Prescriptive, Predictive, Descriptive), Application and End Users | Growth Opportunities and Future Demands

“\”Data Analytics Market\””
Market Research Future published a half cooked research report on “Global Data Analytics Market” – Market Analysis, Scope, Stake, Progress, Trends and Forecast up to 2022

Data Analytics Market – Overview:

Data analytics is of paramount importance for any business. It is a means through which a firm can capitalize on the data that they have collected over the years. When it was first discovered, not many were aware of its numerous advantages. But now, as more and more people are discovering the many benefits associated with it, the demand for this procedure has shot up. This in turn, has provided that much needed push to the global data analytics market.

In simple terms, data analytics is used to interpret and discovery sensible patterns in any given data. This pattern can then be utilized to form a completely new strategy and boost any given business. This procedure is comprehensive and comprises of methods like operations research, statistical analysis and computer programming.

Many enterprise owners invest in data analytics to enhance the productivity and performance of their business. Furthermore, it can also be employed to predict and describe future trends. Additionally data analytics can also aid in making important business decisions or in devising the next plan of action for an organization. All in all, this innovative procedure has so far proven to be a boon for the business owners out there and will continue to be so in future as well.

Market Players & Key Strategies

Some of the most acclaimed names of this industry can be listed as Amazon Web Services, IBM, Looker, Microsoft Corporation and SAS Institute. The two major strategies used by these players to stay ahead in the competitive arena are strategic expansion and investment in research and development.

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Market Scenario

Currently the IT sector is going through a phase in which revolutionary changes are underway. Thanks to this fact, it would be safe to say that the global data analytics market has great future potential. During the forecast period of 2017-2022, the industry is anticipated to reach a whopping value of USD 159 billion. The CAGR rate too stands tall at 31%.

There are many growth propellers that cumulatively drive the market towards its growth and development. The higher need for better ways to tackle the challenges associated to big data happens to act as a chief growth booster for this market. Additionally, the increased demand for business intelligence and analytics will work like a charm for the industry.

Furthermore, aspects like reduce price of cloud deployment models, advantages of data analytics over conventional analytics, rising necessity to tend to data challenges in various industries further foster the development of the market.

Market Segmentation

The worldwide data analytics market has been separated into four equal parts. They can be listed as end users, types, geographies and applications.

On the basis of end users, the market has been divided into healthcare, BFSI, manufacturing, software/IT and government.

When it comes to types the industry is trifurcated into descriptive, prescriptive and predictive.

Geographically, the market has its reach across several areas of the world like North America, Europe, Asia Pacific and Rest of the World.

Lastly, based on applications the market has been segmented into DBMS, mining and data mining.

Target Audience

Data analytics market has a very peculiar target audience that comprises of software developer companies, data analytics companies, big data analytics service providers, service providers, manufacturing companies and analytics service providers.

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Market Trends

At present there are three main trends that the market has high hopes of and they are as follows:

•              Emergence of proficient machine learning algorithms.

•              Better computer systems to analyze large datasets.

•              Adoption of concepts of artificial intelligence and internet of things IoT.

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