The Future of Analytics: 3 Predictions for BI in 2015

A look at business intelligence in the year to come, in light of the latest developments in the industry: data keeps growing, companies demand self-service and agile software, and in-memory technology is forced to face its limitations.

By Saar Bitner, Nov 2014.

As 2014 winds to an end, it’s time to start looking forward. Business Intelligence might not be a household term yet, but it’s certainly gained traction in the business community. With more and more companies understanding the importance of data, business intelligence tools are spreading like wildfire from mass enterprises and tech-oriented companies to SMBs and businesses in a much wider range of industries.

So what does 2015 hold in store for the world of BI? We don’t have the predictive analytics capabilities to see into the future just yet, but we can make a few educated estimations based on current industry trends and developments.

Multiple Data Sources Data Gets Bigger (and Uglier)

The term Big Data is somewhat ambiguous, but there can be no doubt that the amount of data is growing exponentially, and that it is becoming more complex to handle in the process. With storage prices plummeting and automated extraction methods becoming more sophisticated, companies are finding themselves collecting massive amounts of data even when they had not set out to do so in the first place. Much of this data is unstructured and collected in tables which vary wildly in format and size, generated by machines and cloud-based applications rather than employees who follow a particular doctrine of data collection. This means ETL processes are not getting any simpler.

This tendency of data to grow in size and complexity is expected to increase as the use of publicly available data sets becomes more widespread. Amazon and the US government are two examples of organizations which have released terabytes of records collected over time, on diverse subject matter - from public safety to Wikipedia page traffic. Internet of Things

Yet more data is being generated by the Internet of Things, which currently encompasses over 10 billion interconnected devices, a number which is also expected to see significant growth in coming years.

The business world is only beginning to harness the power of external data sources and learning how to gain actionable insights from them; but as knowledge in this area grows, analyzing the data found in these gargantuan repositories is expected to become an integral part of business intelligence.

Thus, in addition to expanding internal data, BI software will also have to take on tremendous amounts of data from external sources.

Agile and Self-Service Business Intelligence

We expect 2015 to be the year of self-service BI. Already we can see many of the industry’s traditional providers touting their newest releases as ‘intuitive’, ‘built for anyone in the company’, etc. This is a response to an actual need within the business community: Users want to control their own destiny and be able to get answers to queries of their choice, without having to call up their IT department for every minor change in needs or definitions. Besides, consumers have gotten used to owning devices and software that ‘just works’ - and expect the same of their BI tools.

The industry will have to adjust itself: BI solutions in 2015 will be expected to be simple enough to provide middle-management and business users, rather than the company’s IT professionals or external consultants, the ability to build and operate a workable BI dashboard in reasonable timeframes.

Implementation times will also have to become shorter: software that takes 6 months of integration and personnel training to become operational could be too much of a hindrance in a world of rapidly changing markets that requires fast-paced insights and decision making.

Furthermore, software will be required to be agile - to adapt to changing business needs, grow with the business and offer users the ability to change their queries and data sources in real-time. Scalability and extensibility will become crucial elements, as a company that currently has 50 gigabytes of data might have 500 gb in a few years’ time.

Alternatives to In-Memory Technology

Since the beginning of the current century, business intelligence has largely been reliant on in-memory technology - i.e., utilizing the computer’s RAM for querying tables. This was the BI industry’s way of handling the reduced performance and long query times that came with analyzing large data stored on computers’ hard disks.

While this solution was sufficient at first, it seems the tides might be changing. Unlike hard drive storage, RAM is still relatively expensive; increasing RAM resources at the pace in which data itself is growing raises serious cost-efficiency issues, particularly for companies that do not enjoy unlimited resources and need to see immediate ROI on their business intelligence projects.

BI providers in 2015 will have to address this issue - either by accepting the limitations of their software (i.e., offering customers the choice between increasing their investment in hardware, using clustered and partial data or learning to live with reduced performance), or by developing technological alternatives to in-memory analytics.

Saar Bitner BIO: Saar Bitner is the VP Marketing at business analytics and dashboard software company, Sisense and executes data driven strategies as he makes way for the massive growth taking place. He has more than a decade of Marketing, Sales and Product Management experience. You can follow Saar on Twitter or connect on LinkedIn.