enterprise data analytics trendsBusiness intelligence continues to evolve as developers unravel the mysteries of big data analytics. A good way to track that evolution is to monitor recent BI and data analytics trends.

What’s Going On in the Big Data Analytics Space?

A lot. Some topics are continuations of familiar changes: falling costs in BI programs and browser-based data analytics, greater access and easier-to-use interfaces, and cloud-based services. Others are new wrinkles, which have appeared in the past several months. We dish up some of each below.

Development of social intelligence.

As social data becomes more of a competitive advantage, businesses are spending more on its analysis. Tracking conversations via social media help firms discover when a topic is beginning to trend and what their customers are saying.

User communities are growing in enthusiasm.

As BI and data analytics tools gain user favor, they create fan bases or communities of SME and enterprise users. Developers in these businesses will probably point to these communities as proof of product usability and value.

“Stubborn” resistance to cloud analytics.

In spite of widespread enthusiasm for cloud analytics, many IT leaders delay uploading sensitive data and continue to work on their onsite machines. Businesses worried that uploading their secure data to a third party server might compromise it can add an extra layer of security and bring advanced business data processing in-house, via the cloud.

News sites are integrating data analytics into their broadcasts.

News outlets are starting to use real-time analytics to provide answers to cultural, sports and business questions—answers that only big data can provide.

More data insight for road warriors.

Big data access and the ability to process it on the road will continue to be a key offering of big data tool vendors. Mobile data processing is not new. But, advances in mobile phone processors and the widening coverage of high speed mobile broadband support real-time communication in the cloud. A positive effect of the migration to mobile enables users to operate these systems and view the results without a mouse or keyboard.

A move away from programming, towards graphical modeling.

This development promises to do away with intimidating code altogether (except for programmers, who might want it). This change would extend the long series of recent developments, which extends the capabilities and user base of big data analytics.

BI and Analytics Reach the Tipping Point

A more level information playing field. The old story: Insights available to data scientists become available to business users. It’s the end of analytics being the exclusive domain of data scientists and power users.

The new story: the power of analytics—once only available to large organizations—is increasingly available to small- and medium-sized businesses. The availability of rich data—video data, low-cost computing power, and analysis and visualization tools—has made a more competitive playing field.

The hybrid cloud will endure.

Many industry watchers agree that the hybrid cloud approach will dominate the enterprise computing space for years to come. Decision makers see the agility and flexibility of the cloud and the value in on-premises data processing. The emphasis is likely to use analytics approaches that take advantage of both resources.

Rise of streaming analytics platforms.

These online environments enable users to decode and analyze data in real time and take action based on insights they gain. These platforms also include data stores, which rapidly ingest large amounts of the new data feeds.

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matt profile -enterprise data analyticsMatthew Winter
Data Scientist
About Matthew: Matthew leverages Business Intelligence tools with his background in Educational Measurement to empower businesses to make data-driven decisions. Recently, his work has been focused in the banking industry analyzing, interpreting, visualizing, and presenting workforce data from over 8,000 employee assessments.

Matthew received a B.A. in Chinese language and literature from California State University Los Angeles, an M.A. in Chinese language pedagogy from Indiana University, and an Ed.M. in Applied Linguistics, Second Language Assessment tract, from Columbia University, Teachers College. Matthew is certified as a Desktop 9 Qualified Associate in Tableau.