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11 market trends in advanced analytics

Thor Olavsrud | July 9, 2014
In today's business environment, organizations are increasingly demanding advanced analytics that allow them to use large volumes and diverse types of data to discover patterns and anomalies and predict outcomes.

"SAP offers an in-memory platform, HANA, which allows customers and partners to run InfiniteSight on hardware that is designed for high-speed and volume analytics," they write. "In addition, IBM's PureData System is an integrated system that is designed and optimized for operational analytics workloads. Customers can benefit from the increased reliability, scalability and speed of an integrated system SAS has partnered with database maker Teradata to offer a pre-integrated and optimized platform."

2. Vendors Are Packaging for Horizontal and Vertical Use Cases

Kirsch says customers are increasingly looking for end-to-end vertical or horizontal solutions and vendors are obliging with solutions specialized solutions for verticals like healthcare, finance and government and horizontal packages aimed at improving customer service, churn reduction or fraud prevention.

"The solutions come pre-integrated with best practices, data preparation automation and automation for model building, but also allow for some customization," Kaufman and Kirsch say. "Some examples of this packaging include SAS' customer intelligence platform that gives customers tools to personalize consumer experience and Pega's extensions for SAP and Pega's offering allows customers to run business process management (BPM) and customer relationship management (CRM) analytics from specific data sources."

3. The R Open Source Programming Language Is Becoming Pervasive

R, an open source programming language for computational statistics, visualization and data is becoming a ubiquitous tool in advanced analytics offerings.

Kirsch says nearly every top vendor of advanced analytics has integrated R into their offering and so that they can now import R models. This allows data scientists, statisticians and other sophisticated enterprise users to leverage R within their analytics package.

One of the big beneficiaries of this trend, Kirsch says, is Revolution Analytics, the leading provider of enterprise support for R. Kaufman and Kirsch also point to advanced analytics firm Predixion, which is focused on extending R beyond data scientists and statisticians to business users through a wizard interface.

4. Python Is Opening the Door for General Purpose Programmers in Advanced Analytics

While R is typically the domain of data scientists who can develop complex analytics models using sophisticated deep data analytics and machine learning, the open source language Python is allowing the much larger body of general purpose programmers to get in on the act.

"While Python does not have the sophisticated deep data analytics and machine learning capabilities that R does, the community is working hard to develop more focused advanced analytics capabilities for Python," Kaufman and Kirsch say. "IBM and SAS both allow customers to integrate R and Python projects into larger projects."

5. Visual Interfaces Are Making Advanced Analytics More Accessible to Business Users

Data scientists are few and far between on the ground, and small and mid-sized enterprises in particular are struggling to create experienced analytics teams due to a lack of budget. At the same time, analytics is working its way into decision-making at all levels of the enterprise, making it more important than ever that business users be able to access data insights. That combination has advanced analytics vendors firmly focused on offering features that make their platforms easier for business users to use.


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