Social networks and social media are ubiquitous! Every aspect of modern life (personal and business) involves sharing and social interaction, whether one is broadcasting information about a recent family event, posting a picture, asking opinions at work or promoting a new product or event.
In the old days, team members and employees shared and discussed information at the water cooler or in the cafeteria. Content Management Systems (CMS) and online meeting software furthered collaboration and sharing and helped business users to come together to review and edit documents and work on projects. And, so it is no surprise that today’s business users expect the same sort of capacity for sharing and collaboration in a business intelligence tool.
Dry reporting and restrictive dashboards no longer serve the purpose of the organization or its users. Driven by the increasing demand for self-serve BI tools and shared resources and knowledge, business intelligence must now support applications of social networking and social media if it is to remain relevant and continue to contribute value to users and enterprises.
Imagine a world where your users can engage in social interaction and collaboration and discuss, rate and comment on data and analytics within reports, dashboards, or key performance indicators (KPIs) – a kind of ‘Face Book for Analytics‘ approach to business intelligence.
The advent of tools like self-serve data preparation, plug n’ play predictive analysis and smart data visualization provide support for business users to leverage sophisticated tools and algorithms in an easy-to-use environment and improve data agility and timeliness. Business users can apply their own domain and role-specific knowledge and skill to data analytics, the availability and access to solid data and creative, concise reporting and data sharing will result in improved user adoption and the emergence of ‘popular’ Citizen Data Scientists and reporting techniques and data presentation.
Users can rate a particular data source, or a particular report or dashboard. Data agility and accessibility is not the same thing as 100% high-quality data produced by analysts or IT resources but for many business applications, self-serve data preparation is just what is needed to achieve good, solid information and perform analysis to make good decisions. Where and when 100% accuracy is required, further research and reporting can be ordered using skilled resources and ETL or DWH techniques. For everything else, self-serve data preparation is a great way to share, rate and popularize data analysis and business intelligence tools and provide timely benefits and return on investment within the enterprise.
Business users can leverage self-serve data preparation in a ‘social networking’ environment that allows for rating, sharing and commenting on data and improves empowerment, accountability and crucial interaction among team members. Your users are no longer looking at dry, static reports in an isolated environment. Instead, they can collaborate and build on the work of others to get the best result and make the best decisions.
Data sharing and rating illustrates the type of data and reporting that is most popular – the data that the most people find the most useful and provides added business value. Understanding the social aspect of data analysis and data popularity, can help IT staff and executives gain insight into what their business user value, and what tools offer the most beneficial support to the organization. This feedback will help the organization plan for additional provisioning, reporting, dashboards, tools, data integration, data watermarking and certification and ETL and DWH configuration, cleansing, and resource management.
This approach allows the organization to balance resources and measure and manage data quality vs. data popularity so that the social aspect of data analysis can work hand-in-hand with the quality data approach to ensure data agility AND data quality.
About Kartik Patel
Kartik Patel is the founder and CEO of Elegant MicroWeb. He originated the ElegantJ BI flagship business intelligence software product, which is a self-serve, mobile BI tool designed to support data democratization and transform business users into Citizen Data Scientists. The ElegantJ BI Advanced Data Discovery, Smarten approach to BI tools, includes Plug n’ Play Predictive Analysis, Self-Serve Data Preparation and Smart Data Visualization. In 2016, ElegantJ BI was listed as Representative Vendor in the ‘Gartner Market Guide for Enterprise-Reporting-Based Platforms’, and noted in the ‘Gartner Magic Quadrant for Business Intelligence and Analytics Platforms.’
Original Source – Social Business Intelligence: The Next Big Thing!