Big Data

Contemporary Technology Trends in Business Intelligence

Over the last few years, Business Intelligence has become the lifeblood of organizations. Big Data, predictive analysis, data science, and cloud services are constantly innovating spaces that feed into business intelligence, continually changing the role it plays within enterprises. But where are we headed next? Here is an outline of some predictive insights into the contemporary technology trends in business intelligence.

1) Self-service Business Intelligence will accelerate

Through 2017,  business intelligence will become easier to use and will gear towards self-service. Self-service information for the masses is expected to be delivered via purpose-built interfaces and applications. With a database like EXASOL, a visualisation tool like Tableau, and a data preparation tool like Alteryx, it is now possible to take the complexity out of data analytics. These tools are allowing business users to run service business intelligence reports.

2) Internet of Things and Real-Time creating new opportunities

The Internet of Things is creating new opportunities for real-time analysis and data visualization. Business intelligence tools that deliver data from connected devices are thriving, and advanced analytics is not just for data experts anymore.  With predictive capabilities becoming prevalent through data analysis, the machine learning realm is becoming accessible to a wider group of regular people.

3) All data becoming equal

Throughout 2017, data value will no longer be tied to its size or rank. What will now count is that individuals can easily and quickly access the data and analyse it alongside other data types to answer business questions. In future, we expect to see business intelligence shifting toward an environment where individuals can analyse data of all sizes, shapes, and types, and share insights to influence decision-making.

4) Data analytics for all people

Gone are the days when IT experts spent time on sharing data through PowerPoint decks and PDFs to relevant teams. Today, employees are increasingly sharing live, workbooks and data sources, helping to drive business decisions easily and fast, thanks to the power of self-service and the availability of visual analytics.

5) The Rise of Application Programming Interface (APIs)

Companies are moving towards a broader use of SaaS apps to replace or complement enterprise applications. As mobile apps continue to increase, there is growing need for APIs and cloud connectivity, with emphasis on productivity and better developer tools. Third-party API companies are increasing, fundamentally changing the dynamics of how software is developed and brought to market.

6) Analytics will be everywhere

To work well, data analytics should be a natural part of individuals’ workflow. Analytics is becoming pervasive and in turn, many businesses are expecting analytics to inform all decisions. This is putting analytics into the hands of individuals who have not previously consumed data– from store managers and call-centre workers, to nurses and doctors– to make data-driven decisions.

7) Collaborative Analytics Taking Centre Stage

We all know that many heads are better than one. In 2017, we are expecting to see collaborative analytics moving from the fringe to the core as governed data become increasingly accessible and cloud technology allows easy sharing.

8) Data analytics becoming the new skill in town

According to a 2015 MIT Sloan Management Review, 40% of the businesses surveyed were struggling to get and retain the data analytics talent. Last year, LinkedIn listed data mining and statistical analysis as one of the hottest skills for a person to get hired.  Data analytics has become not only one of the best skill to have but also a key competency for professional of all types.

9) Analytics moving to the cloud

Organizations are realizing that analytics should live in the cloud. In 2017, we expect data gravity to push business to move their analytics to the cloud, a place where their data is stored. Cloud data warehouses such as Amazon Redshift is expected to be a popular data destinations, resulting in cloud analytics becoming more prevalent.

10) Working with Data in Natural Ways

The interface to data is starting to feel more natural, thanks to improvements in areas such as natural language processing. Natural language interfaces have been added to the business intelligence toolbox. They make data, dashboards, and charts more accessible by allowing people to interact with data using natural language and text.

David Drai, the CEO and cofounder of Anodot recently wrote and interesting article on how Business Intelligence Is Making FinTech Successful. I think you should check it out too here.

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