Analytics in a Fast Data World

There’s a need to enable better decision making today with faster access to data. But many organizations are still weighed down by integration and management processes that are not keeping up with the increasing volume, variety, and velocity of data. A greater emphasis on cloud and self-service tools may provide an approach to remedy the situation.

Here's a look at the current state of BI and analytics and the role of self-service capabilities by the numbers:

The need for faster, more effective information delivery is growing more pressing each day. Data managers and professionals report that:

  • There is strong demand for delivery of real-time information.   57%
  • Analytics is part of the day-to-day decision making.   57%

Source: “Moving Data at the Speed of Business,” 2016 IOUG Survey on Data Delivery Strategies, sponsored by Oracle and produced by Unisphere Research

BI professionals spend the majority of their time getting raw data ready—not analyzing it—and 30% say they spend 50–90% of their time on ETL alone. The biggest challenges are:

  • 55%   Making data analytics-ready by merging different sources
  • 39%   Transforming, cleansing, and formatting incoming data    
  • 32%   Integrating relational and nonrelational data     
  • 21%   The sheer volume that needs to be managed    

Source: Study of more than 200 BI professionals commissioned by Xplenty, 2015

IT and business are aligned on the importance of self-service BI, and yet adoption is still low.

  • 91% of IT and business users acknowledge self-service analytics tools are essential.
  • Only 22% of business users had access to self-service BI tools in 2015, the same as 2014.
  • In 2014, 51% of users had access to the data and information they needed without IT help, but in 2015, only 43% had that access, suggesting that more data from more sources is increasing dependence on IT.

Source: “2015 State of Self-Service Report” from Logi Analytics

Organizations with legacy data management platforms are feeling the pressure of modern analytic workloads and increasing data volumes.

  • 50% of IT leaders say they are not very confident in their existing data infrastructures.
  • 56% say legacy systems are feeling the strain of new workloads.
  • 42% say their data warehousing platform is breaking under the pressure.

Source: Global survey of more than 250 CEOs, CIOs/CTOs, and IT leaders, conducted by Actian Corp. in 2015

New information management, storage, and analytical technologies are moving into the enterprise, but as organizations use more data types from more sources, complexity and risk are escalating.

Technology trends with the most impact on database administration over the next 3 years:

  1. Cloud
  2. Virtualization
  3. Big Data

Source: “The Real World of the Database Administrator,” sponsored by Quest Software and produced by Unisphere Research, 2015

Cloud analytics is reaching a tipping point.Improved quality and consistency of data across systems

Cloud analytics is being driven by escalating end-user requirements for better analytics, according to decision makers who cite the need for:

  • 77%   Better ways to visually explore data
  • 72%   Real-time data aggregation and analytics
  • 70%   Real-time data aggregation and analytics

Source: “The State of Cloud Analytics,” sponsored by Informatica and produced by IDG Research Services, 2015

Image courtesy of Shutterstock.


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