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2019 is the year that analytics technology starts delivering what users have been dreaming about for over forty years — easy, natural access to reliable business information. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s.
As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. In 2019, I wrote the book “Disrupting Data Governance” because I firmly believe […] The post Dear Laura: How Will AI Impact Data Governance? appeared first on DATAVERSITY.
Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. 1) DataQuality Management (DQM).
These systems can already speak, write, read and learn; hence, this is one of the big data buzzwords that will continue to disrupt industries in 2020 as well. As we mentioned in our business intelligence buzzwords article for 2019 , mobile usage is becoming an increasing factor in BI. Mobile Analytics. Graph Analytics.
The fact that only 8% of companies have deployed an AI model into production (according to Gartner’s 2019 AI Maturity report ) is testament to that. Just knowing where to start—let alone how to make it all run sustainably in a production environment—can be difficult. But here’s the thing: Becoming part of that 8% is not impossible.
Ideal for: creating data visualizations and reports for businesses of all sizes, with users ranging from technical beginners to analysts. Tableau Tableau (acquired by Salesforce in 2019) is another top business intelligence and visualization platform.
How will artificialintelligence and other automation technologies evolve? How will artificialintelligence and other automation technologies evolve? For example, professions related to the training and maintenance of algorithms, dataquality control, cybersecurity, AI explainability and human-machine interaction.
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