Driving Innovation through Business Intelligence
Unleashing the Power of Analytics in Academics
Data Science Isn't Just Business Intelligence: Here's How to Cross...
How to Conquer the Last Mile of Analytics
Business Intelligence a Top Priority in 2016, Again?
Ben Stewart, CIO, Stant USA Corporation
Enhancing ROI with Data Visualization in BI and Analytics
Boris Evelson, VP, Principal Analyst, Forrester Research
Business Intelligence that Delivers for Logistics
Paul Schwartz, Director of Information, WSI
Four Ways to Use Business Intelligence in the Boardroom
Jayne Landry, Global Vice President and General Manager, Business Intelligence SAP
Thank you for Subscribing to CIO Applications Weekly Brief
The Latest Business Intelligence Trends
FREMONT, CA: The latest Business intelligence (BI) trends are outlined below as it is a staple of a compelling corporate entity.
Analytics Adoption: Analytics is a new tool for stakeholders to get an understanding of data related to their function and obtain insights. The bottom-up strategy is absorbed as a fundamental part of the BI strategy, enabling users to perform analysis independently.
Cloud-Based Analytics: As the processes are shifting towards cloud-based analytics, data-sharing is streamlined automatically. The various facade of digital transformation, like IoT integration, is easier to initiate without making any additional investments in the infrastructure, while allowing unlimited permission to access raw data.
Data Privacy: The introduction of the code of ethics will ensure secure data sharing, avoid misuse of data applications, and control overzealous conclusions drawn from insights. The ethics involved are cross-disciplinary and apply to data storage, governance, and data use as well. It ensures compliance with guidelines and aids manager in the lookout for inaccuracies and bias
Explainable AI: Explainable artificial intelligence is helpful while seeking an explanation for the obtained result by increasing transparency in AI processes, encouraging users to dig deep into the data to understand the ultimate conclusions.
Natural Language Interactions with Data: With the progress of natural language processing (NLP), the need for facilitation of new data can be carried out by users both experienced and novice by the use of visualizations, other analytics outputs and focus on the related information without the need of an expert.
Actionable Analytics: Actionable analytics will place data wherever it is most necessary in real-time, with the help of APIs and plug-ins to provide insights to and existing software.
Data Collaborations for Social Good: Shared cloud space is cheaper and efficient for combining forces and sharing data to create an impact none could achieve individually.
The convergence of BI and Data management: The role of BI will be to maintain high-quality data, metadata, and associations between various tools connected. Similarly, data governance is more streamlined as data warehousing and management platforms are integrated into BI tools.
Data Storytelling and Data Democracy: Data storytelling is an avenue to foster a culture of conversation around data in which many partners are involved in understanding results. The drift of democratizing data engrosses data scientists for better application of the data to the businesses in conjuncture to an advanced user for better incorporation of analytics to encourage data interdependency.