Gartner 2019 Magic Quadrant for Analytics and Business Intelligence Platforms is out

It’s that time of the year (where the hell did 12 months go!) where Gartner announce the latest version of their Magic Quadrant for Business Intelligence tools, or this year what they call “Modern Analytics and BI Platforms”.

Im always interested in which vendor hits my inbox with a link to the Magic Quadrant first, this year it was the SiSense team, but Qlik was a mere 1 hour and 10 minutes minutes later.

So following my previous years approach SiSense are the winners and you can get your copy of the Gartner 2019 Magic Quadrant for Analytics and Business Intelligence Platforms from their website here:

Can I also congratulate SiSense for only asking me for a MVP number of questions to get the report, well done!.

The Magic Quadrant itself is:

If you interested in comparing the changes have a look at my blog post on last years Magic Quadrant here:

Gartner Magic Quadrant for Business Intelligence 2018 – Augmented Capability will be the New Black

So big legacy suite players are moving down and to the left and newer players are moving to the top right. No surprise there.

And we are seeing the new players expanding their product footprints via acquisition or new product modules. Tableau Data Prep and Qliks acquisition of Podium is two recent examples.

If history repeats we should start seeing the big suite players start to acquire the top right companies, pretending to want to integrate those features to their suites, but those products and features will disappear over time making one wonder if they are really buying those companies to clear out the competition and give customers less choice.

Last year I blogged that Gartner were saying Augmented Intelligence and Natural Language were the new blacks. This year its pretty much the same view:

“As disruptive as visual-based data discovery has been to traditional BI, a third wave of disruption has emerged in the form of augmented analytics, with machine learning (ML) generating insights on increasingly vast amounts of data. Augmented analytics also includes natural language processing (NLP) as a way of querying data and of generating narratives to explain drivers and graphics. Vendors that have augmented analytics as a differentiator are better able to command premium prices for their products”

They do put a 2020 target on these starting to be readily adopted, what I have seen is a lot of vendor postering on these things, but very little market adoption (in New Zealand at least). There are companies such as Trifacta and Waterline Data that have Augmented Intelligence at its core by recommending to the user what they can do next based on the profile of the data and what the global wisdom of the crowd has done with similar data. And no doubt there are many many startups in “stealth” mode which seems to be the new black about to launch into the noisey world of AI hype.

Gartner has a number of forecasted metrics that allow us to see if the 2020 target is achieved.

“By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence, data science and machine learning platforms, and embedded analytics.

By 2020, 50% of analytical queries either will be generated via search, natural language processing or voice, or will be automatically generated.

By 2020, organizations that offer users access to a curated catalog of internal and external data will derive twice as much business value from analytics investments as those that do not.

By 2020, the number of data and analytics experts in business units will grow at three times the rate of experts in IT departments, which will force companies to rethink their organizational models and skill sets.

By 2021, natural language processing and conversational analytics will boost analytics and business intelligence adoption from 35% of employees to over 50%, including new classes of users, particularly front-office workers.”

I look forward to my blog post on the 202 Magic Quadrant next year, or maybe the 2021 one.

The Magic Quadrant focus has morphed overtime as the market moved from BI Suites to Data Discovery tools. Gartner’s current definition of the market is:

“Modern analytics and business intelligence (BI) platforms are characterized by easy-to-use tools that support the full analytic workflow — from data preparation and ingestion to visual exploration and insight generation. They are most differentiated from traditional BI platforms by not requiring significant involvement from IT staff to predefine data models or store data in traditional data warehouses (see “Technology Insight for Modern Analytics and Business Intelligence Platforms”). The emphasis is on self-service and agility.”

Self Service and Agility mmmmmmmmm.

When I go to the checkout at the supermarket and either go the counter with a person who does it all for me (what Eckerson terms Silver Service) or I go to the counter where I scan the items myself (what Eckerson would call self service), the key is I don’t need any technical expertise to serve myself. But with the latest and greatest of BI tools, while you no longer need an IT specialist to perform the task for you, you still need a high level of technical competency to deal with both the tools and the challenging gifts data always gives us.

So I welcome the day where Augmented Intelligence and Natural Language allows me to ask a just ask a question of my data and get an answer as easily as I can scan my groceries at the checkout.

It does seem lots of people think ChatBots are the answer for this (hence the header photo) and maybe they are. But i’m not convinced.

I believe we need a different paradigm that starts with a way of working (patterns, approaches, methodologies, valuable practises, what ever you want to call it) and technology that supports that way, as we move towards using the user behaviour data gathered (BI on BI say what!) to determine the best way for Augmented Intelligence and Natural Language to provide users true insight self service. Something I am going to personally work on combining in 2019.

I was sure I had blogged many years ago on 5 things that BI would deliver in the near future, and that SearchBI was one of those things. I found this blog from 2012 but looks like I treated it as a backlog and never delivered the series. I remember back in those days where we tried to integrate the yellow Google search appliance into a BI tool (think it was SAS Web Report Studio or Oracle Discoverer back then). Good to see after 7 years we are getting close to be able to use search within our BI tools, who would have thunk’d it.