Modern-day Business Intelligence tools are largely dominated by self-service capabilities, providing a wide audience of users the appropriate features they need to get their jobs done. This is a complete contrast from the past where software solutions were dominated by advanced functionality that only the very few technical users could understand.

In the final iteration of a three-part presentation series, Data Analytics software vendor Phocas shares their view of what Business Intelligence tools will look like in the future (see past and present). Without giving too much away, let’s just say that the cloud plays a heavy role, delivering feature capabilities at a lower cost with faster deployment and flexibility. In addition, the company believes that the practices of discovering insights from data will continue to expand, producing an environment of increased collaboration which will lead to the rapid proliferation of Advanced Analytics in the enterprise.

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Check out this presentation, courtesy of the folks at Tableau, where you’ll discover why government agencies near and far are investing in modern BI platforms and what the future has in store for analytics in the public sector.

Want more? Check out this post in the Center for Open Data Enterprise‘s blog.

The post Visual: Top Government Business Intelligence Trends for 2017 appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

Check out this presentation, courtesy of the folks at Sisense, where you’ll discover why organizations need to invest in BI to begin with, just how companies are deriving value from analytics, how to build an internal business case for new deployments, and much more.

The post Developing the Business Case for Business Intelligence appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

Check out this presentation by the folks at Tableau Software, one of the top providers of analytics software in the world. The slideshow features a culmination of opinions and observations of experts in the field. Where are we headed in 2017? Here are Tableau’s predictions:

The post Top 10 Business Intelligence Trends for 2017 appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

Modern-day Business Intelligence tools are largely dominated by self-service capabilities, providing a wide audience of users the appropriate features they need to get their jobs done. This is a complete contrast from the past where software solutions were dominated by advanced functionality that only the very few technical users could understand. The result, as Phocas explains, is end-users making more informed decisions, and benefiting the business as a whole.

The post Business Intelligence Through History: The Era of Self-Service appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

Fast-forward to 1989 and the term “Business Intelligence” is coined by Howard Dresner, and can be defined as “a broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better decisions.” This presentation is the first in a series by Phocas, in which they outline the history of Business Intelligence, from inception to modern-day innovation.

The post The Historical Roots of Business Intelligence appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

For 3 more scenarios where Predictive Analytics are a must, click here.

The post The Benefits of Utilizing Predictive Analytics in E-Commerce appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

According to TIBCO’s SVP of Analytics Mark Palmer, there are 7 use cases where Apache Spark can and should be applied to predictive analytics. The following slideshow, which Palmer presented at the 2016 Hadoop Summit, dives deep into the ways that the Big Data framework can be executed in a data environment. Spark enables enterprise organizations to access diverse data sources in disparate environments, and data-driven companies are increasingly deploying it in creative ways. Palmer cites the ways in which some of the top companies in the world are utilizing the technology to provide users with agility, reliability, and faster time-to-insight.

The post Predictive Analytics: 7 Use Cases for Apache Spark appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

The post The 6 Worst Practices in Business Intelligence appeared first on Best Business Intelligence and Data Analytics Tools, Software, Solutions & Vendors .

This slideshow presentation, courtesy of the innovative folks at SAS looks at how organizations will handle growing data volumes in the future, part of this, cleverly, involves a good deal of automation.

We know that the amount of data that we’re creating is exploding. Organizations, especially those in the enterprise, are having increased trouble in dealing with all this data. According to SAS, the future of data management could reside in the arms of self-service, where one-person, without being an expert, can do more.

SAS once again remained a member of Gartner’s 2015 Magic Quadrant for Advanced Analytics. Find out what Gartner had to say about the BI giant in this year’s report by clicking here.

Credit to LinkedIn’s newest tool, SlideShare, for hosting this presentation.

Check out these additional resources:

2016 Business Intelligence and Data Analytics Buyer’s Guide

BI and Data Analytics Buyer’s Matrix: Comparing 28 Vendors Features

Gartner Magic Quadrant for Enterprise BI and Data Analytics

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