Gartner business intelligence definition

#GARTNER BUSINESS INTELLIGENCE DEFINITION DRIVERS#
#GARTNER BUSINESS INTELLIGENCE DEFINITION DRIVER#
#GARTNER BUSINESS INTELLIGENCE DEFINITION FULL#

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. The emphasis is on self-service and agility.' 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 вЂњTechnology Insight for Modern Analytics and Business Intelligence PlatformsвЂќ).

#GARTNER BUSINESS INTELLIGENCE DEFINITION FULL#

'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. Gartner's current definition of the market is: The Magic Quadrant focus has morphed overtime as the market moved from BI Suites to Data Discovery tools. I look forward to my blog post on the 202 Magic Quadrant next year, or maybe the 2021 one.

#GARTNER BUSINESS INTELLIGENCE DEFINITION DRIVER#

'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.Д«y 2020, 50% of analytical queries either will be generated via search, natural language processing or voice, or will be automatically generated.Д«y 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.Д«y 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.Д«y 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.' Gartner has a number of forecasted metrics that allow us to see if the 2020 target is achieved. 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. 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.

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).

Vendors that have augmented analytics as a differentiator are better able to command premium prices for their products'

#GARTNER BUSINESS INTELLIGENCE DEFINITION DRIVERS#

Augmented analytics also includes natural language processing (NLP) as a way of querying data and of generating narratives to explain drivers and graphics. '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. Last year I blogged that Gartner were saying Augmented Intelligence and Natural Language were the new blacks.

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. Tableau Data Prep and Qliks acquisition of Podium is two recent examples. No surprise there.ДЄnd we are seeing the new players expanding their product footprints via acquisition or new product modules. So big legacy suite players are moving down and to the left and newer players are moving to the top right. If you interested in comparing the changes have a look at my blog post on last years Magic Quadrant here:

Gartner business intelligence definition