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A Changing of the Guard: BI’s Shift Towards Self-Service

Guy Levy-YuristaIn this special guest feature, Guy Levy-Yurista, Ph.D., Head of Product at Sisense, discusses the increasing shift in BI and data analytics towards self-service solutions. Guy carries a unique mix of skills acquired over 25 years of experience in startup, venture capital and Fortune 500 environments, and specializes in commercializing advanced technologies in dynamic market environments. Prior to Sisense, he served as the executive vice president for the Usher Mobile Identity program with MicroStrategy, where he productized and launched a powerful Identity Intelligence tool. Guy holds a Ph.D. degree in Physics from the Weizmann Institute of Science, in Rehovot, Israel, and an MBA degree from the Wharton business school in the University of Pennsylvania.

More data has been created in the last two years than in the history of the human race. Big Data is a real and present challenge companies in all industries are facing – from financial services and healthcare to hospitality and retail. The ability to leverage existing data quickly to fuel business decisions is more important than ever.

For many companies, aggregating and analyzing data in a meaningful way can be a daunting feat, requiring a great deal of time and too many IT resources to extract business value from data insights. Additionally, as data becomes omnipresent across industries and company size, organizations are increasingly facing an even greater challenge: time – they need to be able to make smart decisions fast. In the hospitality and travel sector, there is no longer time to wait weeks or even days for customer data and travel patterns to be analyzed – those insights are needed within a few hours to engage the next customer, and fend off competitors. Even more critical, retailers are being forced to make decisions as fast as possible in today’s one-click shopping culture where consumers make purchase decisions in only seconds or minutes. Being armed with the tools and insights to adjust campaigns and reach consumers in this fast-paced environment can be the difference between missing sales goals, and exceeding them.

To achieve faster time-to-insights, the business intelligence market has seen a shift in recent years towards self-service technology solutions that help organizations of all sizes better analyze their data, without the need for heavy IT involvement.

The Growth of Data is Redefining the Business Intelligence Landscape

In the data era, where a one-year old startup has as much data as a Fortune 50 company did 20 years ago, this shift is hitting a tipping point. The need for faster time to insights is redefining the entire business intelligence landscape, as shown in this year’s Gartner Magic Quadrant for Business Intelligence and Analytics. The 2016 Magic Quadrant is proof that this isn’t your grandfather’s BI market anymore, as those “old reliable” solutions from legacy companies are being left out of the analysis to make room for more innovative players that are looking for ways to increase agility by putting the power of data analytics in the hands of business users. Ultimately, this quadrant shift led to a dramatic conclusion: Gartner has changed the very definition of what constitutes a modern business intelligence platform. According to the Gartner MQ, “buying decisions are now being made, or heavily influenced, primarily by business users that demand easy-to-use and easy-to-buy products that deliver clear business value and enable powerful analytics with limited technical expertise without required up-front involvement from IT.”

This market shift indicates a trend we’ve been seeing for years – as the amount of data we manage grows, it also becomes more complex. Businesses aren’t just dealing with large sets of data – they have to pull these large data sets from multiple, disparate sources and try to create a holistic view. The obstacle with this is that most tools require significant IT involvement before you can actually analyze the data from multiple sources. This is why agile technology that can marry together data from multiple sources quickly and easily is crucial to extracting business value from data.  Think of a retail organization – they need to pull in data from Salesforce, Marketo, mobile traffic, MS Excel, etc. If you’re not analyzing all of these channels, you’re not getting the whole picture to pull accurate insights. Furthermore, as mentioned earlier, the need for this data to be mashed up quickly is critical for companies to remain competitive in the market.

Self-Service Tools Can Empower Companies to Become Data-Driven

Businesses want the power of data insights to penetrate throughout their entire organization, and not be stuck in limbo waiting for IT’s help. They want solutions that can have a powerful, real-time impact, while still being easy-enough for the everyday business user to use – no matter what their department. There are a host of new possibilities for the non-technical and less-technical to perform their own analysis and find their own insights: from visualization tools for simple, spreadsheet-style data, to new possibilities for mobile and collaboration, and even data analytics software that makes the preparation and analysis complex data, simple.

As the amount of messy data that organizations accumulate continues to grow at exponential rates, organizations that come out on top will increasingly be those that are leveraging the power of data insights to drive business value. By removing the need for specialized IT involvement, data-driven insights are more accessible to the everyday business user – making this an exciting time for business analysts. The shift towards self-service analytics solutions only further validates that we are headed towards a data-driven business landscape. In the decades to come, organizations that succeed will be those who embrace an agile data-driven approach to business decisions, and those who remain reliant on IT departments to prepare and analyze data will be left in the dust.

 

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