There are pivot moments in life and in business where you just know – everything is about to change.
Remember the first time you used the internet, email, a Mac, an ipod, iphone or ipad, or wore Reeboks? OK, I’m dating myself, but before Reeboks, we actually did what we is now call aerobics or cardio classes in bare feet on wood dance floors in ballet studios with leg warmers! Reeboks made it possible for aerobics classes to become main stream beyond its dancer beginnings.
In BI we have had our seminal moments too. Like when Oracle acquired Hyperion in March of 2007, which set of a series of acquisitions –SAP of Business Objects October, 2007 and then IBM of Cognos in November, 2007. Or when Tableau and Qlik’s serious entry into the market circa 2004-2005 set in motion a seismic market shift from IT to the business user creating the wave of what was to become the modern BI disruption. After five minutes of seeing these products back then, I just knew they would change everything!
And here we are now, past the tipping point of a more than 10 to 11 year transition away from IT-centric reporting platforms to modern BI and analytics platforms that make up much of the new buying in the BI and Analytics market. Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption.
A modern BI platform supports IT-enabled analytic content development. It is defined by a self-contained architecture that enables nontechnical users to autonomously execute full-spectrum analytic workflows from data access, ingestion and preparation to interactive analysis, and the collaborative sharing of insights.
By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities.
Since the Gartner BI and Analytics Magic Quadrant has consumed much of my life for the past 8 years at Gartner, it’s only fitting that my very first blog post would be on this (fascinating!) topic.
This past Tuesday, my amazing colleague Cindi Howson and I conducted a Webinar, “Using The BI and Analytics Magic Quadrant To Modernize Your Capabilities”. You can see it On Demand here .
We didn’t have time to get to all the great questions, so below are a few responses, plus some really interesting results from the webinar poll.
Moving to Modern
The webinar polling results are pretty consistent with what we are seeing in our client inquiries: Despite the significant investments you’ve made in traditional platforms and your very valid concerns over how to deploy self-service to all your business users without creating chaos, the vast majority of you are modernizing. A whopping 90% of respondents are either just getting started with or planning to significantly grow their analytics portfolios for business-authored analytics content. The reason is very simple –business people are using modern BI platforms to rapidly derive insights from data in time to create business value in a way that just was not possible with traditional BI tools. These intentions are also reflected in Gartner’s previous webinar poll results in March and in our 2015 market share results, which show a 63% growth in Modern BI market growth versus a 1.7% decline in traditional BI (See: Market Share Analysis: Business Intelligence and Analytics Software, 2015 ).
Importantly, modern BI platforms are not just being used for self-service. An impressive 63% of respondents plan to expand IT-authored content using Modern BI Platforms. Why? Because modern BI platforms allow IT to deliver content to business people faster. And as modern BI platforms improve their enterprise features around governance, extensibility, scheduling, alerting and printing, we see customers using them for both mode 1 system of record analytics AND mode 2, agile and iterative self- service.
It’s also pretty clear that a large percentage of data and analytics teams are shifting their roles from being content authors and data gate keepers to content enablers in support modernization. This is so great to see because this change in focus will be critical to successful modern BI deployments and must include not only IT provisioning curated data sets, but also providing ongoing tools and data literacy skills training and communities for collaboration and sharing.
What Happened to Tradition BI?
Conversely, IT authored enterprise reporting (not modern) is being reduced or maintained by over 60% of respondents, while 38% of respondents still intend to increase their use of non-modern, traditional reporting! The risk of switching existing system of record reporting that is working may be higher than the benefit, so the 45% of you maintaining these systems makes sense, but increasing users and content? While there are some very valid reasons to do so, we probably need to talk.
Some Additional Questions and Answers
Below are some detailed responses. Cindi answered some others, so you’ll have to visit both of our blogs to get the full scoop… Here is the link to Cindi’s.
Q1: Please summarize the characteristics of IT-centric Reporting and Modern BI Platforms .
What are the top 3 differentiating characteristics?
Answer: The primary differences are described in detail in our research, Technology Insight for Modern Business Intelligence and Analytics Platforms and summarized in the table below from the report.
Table 1. Summary of Differences Between Traditional and Modern Business Intelligence Platforms by Analytic Workflow Component
Q2: Would you consider Sisense better than others in handling big and unstructured data?
Answer: Better than every other vendor? Not sure about that, but Sisense is well suited for easily harmonizing, combining and modeling many different, complex and large data sets for fast interactive analysis. Sisense supports a wide range of relational, NoSQL and big data sources. You can read about them in the Magic Quadrant for BI and Analytics Platforms and in the Critical Capabilities for BI and Analytic Platforms .
Q3: Do you identify those modern BI tools that complement each other or where the vendors have collaborated with integration. For instance, Alteryx integrates with Qlik?
Answer: We discuss complementary partnerships like Alteryx’s partnerships with Tableau, Qlik and Microsoft Power BI in the Magic Quadrant for BI and Analytics Platforms and in the Critical Capabilities for BI and Analytic Platforms .
Most of the standalone self-service data preparation tools like Paxata, Trifacta, DataWatch, and Lavastorm partner with Tableau, Qlik and Microsoft Power BI. You can read about this in an upcoming Market Guide for Self-Service Data Preparation that should publish in a couple of weeks…Birst also partners with Tableau allowing Birst customers to use Tableau against Birst’s governed metadata layer. Tools like Analytics8 enable Tableau, Birst, Tibco Spotfire, QlikView and QlikSense to consume SAP BusinessObjects data through accessing the universe. We expect that many other traditional BI players will follow Birst in opening up their semantic layers to leading modern BI platforms so customers can leverage those investments while serving business users. See: The Rise of Data Discovery Has Set the Stage for a Major Strategic Shift in the BI and Analytics Platform Market for a discussion of this topic.
Q4: Are we going to discuss Predictive types of Analytics in this discussion?
If predictive analytics is you prime area of interest, The Magic Quadrant for Advanced Analytics platforms covers capabilities for the analysis of all kinds of data using sophisticated quantitative methods (such as statistics, descriptive and predictive data mining, machine learning, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover.
That said, modern BI platforms include embedded advanced analytics, a critical capability that enables users to easily leverage advanced analytics capabilities that are self-contained within the platform itself to support drag and drop functions like forecasting, clustering and trending, building advanced calculations using statistical functions or the import and integration of externally developed models. Again, check out the Critical Capabilities for BI and Analytic Platforms for how each vendor compares.
Wow, this was really fun… Now that I am all hip with my own blog, I will probably do this more often! We are on the cusp of the next wave of BI market disruption beyond the current one started by Tableau and Qlik – but that’s for my next blog post.
Enjoy your summer. Thanks for reading and stay tuned.
Research VP, Business Analytics and Data Science