In recent years we have seen huge growth in the area of data visualization with new tools rapidly entering the business intelligence (BI) market.
The most well-known among them include Tableau, Qlik (QlikView and QlikSense), Spotfire, Microsoft PowerBI, MicroStrategy, SAP Business Objects and Cognos BI.
Each of these tools has its own strengths and weaknesses; organizations using these kinds of tools aim to add value to organizational decision-making by visualizing important information and BI. Hence, business intelligence and data visualization go well beyond simple KPI reporting. Organizational strategy and other business-related decisions, such as expansion, disruption, hiring, moving, shifting and change, are increasingly shaped by the information extracted from these tools.
Organizations have come to consider data as essential for driving business. As such, they are stepping up their game to gather a plethora of data from their customers, suppliers, competitors as well as the general market to assess and influence their own position and market share. And companies are getting smarter about these processes as they hire experts with the knowledge and skills to drive their data strategy and systems.
At first glance, BI and data visualization tools may appear similar. Take a closer look and we notice significant differences between them. As stated earlier, each has its strengths and weaknesses. But common to all of them is the need for data and underlying databases where the data lives.
These databases are a crucial element in the process, but why?
The importance of performance
Your BI reporting lives and dies with the performance of your database, especially in fast-paced environments where real-time or near real-time insights are required.
The right database can make your reports and data visualizations come to life and guarantee an excellent user experience through fast load times (i.e. no buffering or delays), highly responsive filters and actions and the ability to report in real time. Ultimately these high-performance factors define both the immediate positive user experience and the likelihood of long-term success for your BI and reporting strategy.
Your end-users don’t necessarily know, understand or even care why a report is running slow or taking two minutes to load. They don’t care that even the best-designed report can be crippled by an underperforming database. All they want and need is a report or dashboard that responds instantly to any changes they make to a filter or selector. They don’t want to wait. Users may start side-stepping your solution, creating their own reports, ignoring those your team has created, potentially even leading to your having to justify your data visualization tool decision.
Performance is an expectation that users don’t want to have to think about; it only surfaces when poor database performance forces users to do anything but their work, e.g., chase Pokémon while waiting for reports to load. Performance is key but invisible as long as it is fast and seamless. The expected outcome, which users do think about, is engaging and beautiful visual reports that highlight facts and support sound decision-making. To an organization, how it achieves this outcome is immaterial – I have seen numerous situations in which trying to explain the database constraints to business users fell on deaf ears. Sometimes the decision-makers choose to abandon a project rather than invest in the right database technology to guarantee a successful outcome.
Supercharging your data engine
With the right database powering your BI tool users benefit from stunning visuals and engaging reports that serve up all the relevant information right now. No waiting required.
You can enable faster decision-making, instant feedback to business units on their results, and remove delays in delivering crucial information to key users and stakeholders to ensure that they can be responsive to changes in the competitive environment. And most importantly you can free up people’s time, which can lead to productivity increases and cost reductions.
Instead of having your accountants wait around while your data cube refreshes and avoiding touching Excel for fear it may crash under the load, give them data instantaneously, so they can analyze, investigate, report and recommend. Instead of having your database administrators get grey hair trying to tune your existing database through marginal improvements, let them focus on things like data security, maintaining your overall system health, data backups, storage and capacity planning.
And when they’re done they may well want to have a coffee. And chase Pokémon.