February has come around again, the Gartner BI conference is running in Sydney Australia, people I know are in Sydney drinking beer, I am not, and the Gartner Magic Quadrant for Analytics and Business Intelligence Platform is out.
Can I take a little space to rant (of course I can it’s my blog post) I would really like Gartner to change the title of this to be Gartner Magic Quadrant for Business Analytics and Business Intelligence Platform. The reason is that there is still a big difference between Business Analytics and Advanced Analytics capabilities.
Anyhow the 2018 Gartner Magic Quadrant for Analytics and Business Intelligence Platform looks like this:
The report is available from the SISense website again this year. (Again thank you to the SiSense team for making it available so quickly and apologies for never actually using your product)
Changes and Thoughts
The 2017 Magic quadrant looked like this:
Overall not a major change between 2017 and 2018. Again we see the top three visual discovery vendors, Tableau, Qlik and Microsoft extend the gap in the leaders quadrant.
IBM slips a little lower, SAP climb a little higher and Microstrategy make a move in the challenger’s quadrant to be on their lonesome. But overall no radical changes, like we have seen over the previous few years.
So let’s look at some of the context around the quadrant.
Gartner is again saying augmentation is going to be the new frontier for Business Analytics and Business Intelligence.
“By 2020, augmented analytics — a paradigm that includes natural language query and narration, augmented data preparation, automated advanced analytics and visual-based data discovery capabilities — will be a dominant driver of new purchases of business intelligence, analytics and data science and machine learning platforms and of embedded analytics.”
For me, I see two areas that will emerge as the new black.
Augmented data understanding
At the moment we still rely on a specialised data modeller or a bunch of savy data analysts to understand the data that lives in Systems of Record. In the next paradigm machine learning algorithms will be abe to provide us suggestions on how to prepare and structure the data based on the way the data looks and behaves.
We are all used to asking Google a very bad question and relying on it being smart enough to find us a resoanable answer. In the next paradigm we will finally have mature BI tools that will enable users to ask a business question and get an answer.
I know of a number of startups that have built some of thee capabilities already. It would be interesting to see if Gartner dropped the criteria around revenue and number of customers, how the Magic Quadrant would look when those companies were included.
Gartner are saying that Cloud deployments are finally past the tipping point:
“Cloud past the tipping point. Analytics and BI in the cloud is now past the tipping point. Most net new deployments originating in the cloud, and more than 70% of this year’s reference customers, are already using a public or private cloud (versus just over 40% in 2017).”
It is something I see here in NZ, but what is intersting is that the Vendors are still way behind in their mature offerings. The best we get from most of them is a SaaS offering if you are a small customer and can live with a cut down version of the product, or a Private Cloud version that is provided as a Managed Service.
Hopefully we will start to see true PaaS offerngs emerge this year from these vendors.
BIG Data Tools
Datameer and Zoomdata made the Magic Quadrant last year, which to me indicated we were finally seeing visualisation tools becoming available on the Big Data ecosystem.
But this year they disappear again. Gartner state:
“ClearStory Data and Zoomdata were excluded because they did not meet one or more of the inclusion criteria for this year’s Magic Quadrant. Datameer and Pentaho were excluded because they shifted their market emphasis.”
Intersting Alteryx have also dropped out, with Gartner stating:
“Alteryx was excluded based on Gartner analyst opinion formed in inquiries, customer reference checks, reference surveys, and industry events that they primarily complement rather than compete with other vendors in this Magic Quadrant. They are included in the Magic Quadrant for Data Science and Machine Learning, as well as in the Market Guide for Self-Service Data Preparation.”
This reinforces the view that the gap right now in the Big Data space is easy data acquisition and data manipulation capabilites that can be created and executed by less technical users (citizen data scientists).
For now it looks like we will be stuck with Apache Drill and its elk for query Big Data and then extracting and loading the results Ito the visual data discovery tools.
At the end of the day and to be perfectly honest …
For me it reads as a statement of transition indicating a shift from the current visual data discovery leaders to a emerging augmented data and visualisation world.
Intersting Gartner peg the MegaVendors as the ones that may end up winning that race.
“The 2017 Magic Quadrant showed that many megavendors late to visual-based data discovery disruption were early to the third wave of disruption in the form of augmented analytics.”
“During the next several years, buyers will benefit from significant market investment in innovation from large vendors, as well as from venture capital investment in innovative startups”
I can’t wait until next February. But I think I might go to Sydney for that beer in 2018.
Change, learn or fade away, it’s your choice – Shane
Most of my time is spent teaching and coaching customers how to deliver using AgileBI as part of the Optimal Orange team.
We run regular Agile courses with a business intelligence slant in both Wellington and Auckland, you can learn more about these here.