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Big Data Discovery Is The Next Big Trend In Analytics

It's the logical combination of three of the hottest trends of the last few years in analytics: Big Data, Data Discovery, and Data Science.

Each of these areas has seen explosive growth, but there are clear upsides and downsides to each. For example, Data Discovery excels in ease of use, but allows only limited depth of exploration, while Data Science provides powerful analysis but is slow, complex, and difficult to implement.
Since the disadvantages of the three technologies map to nicely to the advantages of the others, they are now starting to blend, and Gartner believes Big Data Discovery will be a distinct new market category by 2017.

The emerging Big Data Discovery tools will be simpler to use than data science products and accessible to a wider ranger of users, with more powerful manipulation of a wider variety of data sources.

According to Gartner Analyst Joao Tapadinhas, these tools will be used by new "Citizen Data Scientists" who marry the skills of traditional business analysts with some of the expertise of expert statisticians.
These users would not replace existing data scientists, but complement their limited availability to expand the use of these powerful new technologies to more business opportunities.
The company provides a fast, in-memory platform called SAP HANA that includes various Big Data analytic engines, including predictive analytics, and links to open source platforms such as Hadoop and Spark.

The SAP Lumira data discovery product runs on top of the platform to provide self-service data manipulation and visualization, and integrates tightly with the latest SAP Predictive Analytics 2.0 product. The latter combines a traditional advanced analytics workbench with the famously easy-to-use automated data preparation and mining of the SAP Infinite Insight product.

In addition, SAP is taking things to the next level. After carrying out co-innovation projects with customers, the company has created new packaged business applications such as SAP Predictive Maintenance. The application uses combines sensor data access, embedded data science algorithms, and traditional business measures to create new best-practice business processes.

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