Anyone who's seen the most recent Business Intelligence and Analytics MQ report from Gartner would probably agree that conditions are ripe for a major shakeup in the $71 billion BI industry. 

Legacy business intelligence software has been around for decades and still has failed to make data more accessible for front-line business people. In fact, employees wait for weeks — or months in some cases — for teams of data experts to build and curate reports that answer their data questions. Can you imagine waiting that long as a consumer? So why is the bar so much lower in the workplace?

This year Gartner moved almost every vendor out of the MQ leaders quadrant and created an entirely new category for legacy BI vendors called enterprise-based reporting platforms.

The arrival of modern BI platforms on the scene promises to once-and-for-all eliminate the analytics bottleneck. These tools aim to streamline decision making by giving front-line business people direct access to their data with the usability we’ve all come to expect of consumer technologies.

Modern BI software poses a real threat to the continued existence of legacy BI vendors, but these legacy vendors continue to make the same promises of usability and ease of access to data that have been made for years.  

Before giving your legacy BI vendor another chance, ask if they can deliver on the four key capabilities of modern BI — preparing data for analysis without ETL, automatic and optimal organization of data in-memory, self-service report development and end-user report refinement. If the answer is no, it’s time to make the change that puts the power in the hands of your front-line business users.

Remove Lengthy ETL Transformations

BI professionals spend up to 90 percent of their time just building and maintaining ETL processes. Most business intelligence tools were designed decades ago for a much simpler data environment and haven’t kept up with the rapidly evolving enterprise data landscape. 

Data experts are stuck transforming data to fit into a specific schema (like a star schema) for operational reporting, resulting in the weeks or months lag time between query and answer — even for the simplest data questions. Schema flexibility and self-service data integration eliminate this type of bottleneck. You connect enterprise data as is, regardless of its source, be it data warehouse, cloud applications, spreadsheets or Hadoop. 

Instead of doing complex transformations and integrating data sources inside expensive, complicated ETL software, modern BI allows you to create links between data sources on-the-fly from within your BI environment. Business users can define their own key metrics, freeing up BI teams to focus on more strategic analytics and more complex data sources.

Automate Data Organization

You should never have to sacrifice data richness for performance. In the legacy BI world, data professionals can spend weeks manually indexing data in-memory and creating aggregate data structures like cubes and materialized views, sacrificing valuable details in their data to optimize for performance. 

By automatically optimizing the way data is organized in-memory, modern BI tools deliver faster performance, regardless of the amount of data in your environment. This gives end-users users the freedom to explore their data in any dimension, drill deeper and ask follow-up questions on-the-fly without having to reenter another reporting queue.

Put the Power in Line of Business Users

In the legacy BI world, data experts have all the power. After building a data pipeline, BI and IT teams spend most of their time helping end users connect key business metrics back to the logical data model. This typically involves creating a semantic layer that gives end users a more business friendly view of their data — complete with security rules, calculated fields and hierarchies in an effort to simplify the path to insights. 

Unfortunately, this makes for a rigid analytics experience. 

Users have no flexibility to explore data outside a predetermined discovery path. Modern BI platforms do things a little differently. Because data has already been optimally organized in-memory at load-time, users can drill down and across any dimension without any limitations. Users can define synonyms and create formulas using natural language to start conducting more advanced analytics. 

These modern tools also synchronize enterprise group and field-level permissions with your existing security software, ensuring compliance without sacrificing data accessibility.

Blur the Boundary Between Insight Consumers and Creators

Few reports are finished after the first go-round. 

With legacy BI, this often means taking weeks and several iterations of a report to get BI queries to precisely answer end-user business questions. Data visualizations that make data insights digestible and actionable or the simplicity of consumer tech with which they’re already familiar, such as search. For example, if you need to change your analysis for the last two months to the last two years, Modern BI won’t force you or your BI team back to the drawing board — it’s as simple as dragging and dropping a new filter to create a new chart or typing a few words into a search box.

For those wondering whether they are locked in a loveless relationship with legacy BI, answer this question: Does your current solution require ETL transformations to catalogue and load data, fails to automatically optimize the organization of data and prevents end users to, build or refine reports themselves? If so, chances are you’re stuck. The spark is gone, and it’s probably time for you to investigate whether a modern BI could make your love for BI bloom again.

Title image by Jean Gerber