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Let’s talk about the application of social media and social networking within the Business Intelligence environment. This might seem like an odd concept but give it some thought. Every consumer and business user is now used to the idea that they can share, rate, discuss and learn from others. This idea has become an expectation and it could and should apply to Business Intelligence (BI) and to your business users as well!
A BI tool that supports mobile, self-serve data preparation, plug n’ play predictive analysis and smart data visualization will provide business users with sophisticated tools and algorithms that are easy-to-use and provide access to data that is easy to share and personalize. Business users can use these tools to become Citizen Data Scientists and in so doing, an organization will begin to see the emergence of power users who take a creative, insightful approach to data analysis. When users can share this data in reports and dashboards, the next logical step is to allow those users to comment on, share, and recommend data, reports and analysis.
Just as social media users can ‘Like’ or ‘Share’ a provocative post from another user, a social business intelligence tool can support the same kind of sharing and learning within your organization. As power users, and data analysis, become ‘popular’, the enterprise will see improved user adoption of BI tools and, more importantly, will begin to understand what types of data users value, and how to provide and present data to improve data leverage, and increase confidence in decisions.
Understanding the social aspect of data analysis, and data popularity, can help IT staff and executives gain insight and offer the most beneficial support to the organization. This feedback allows the enterprise to make decisions about additional provisioning, reporting, dashboards, tools, data integration, data quality watermarking, ETL and DWH cleansing and configuration, and skilled resource management.
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Imagine an environment where users can access a business intelligence and analysis portal and see popular data to rank and share and comment. This type of sharing can optimize resources by allowing users to access reports and data that might be just what they need to complete a task or analysis. If they don’t have to reinvent a report, they can optimize their time. Popular, agile data and analysis can also free up your IT resources and data scientists to perform more important tasks. If and when business users need high quality, 100% concise data, they can reach out to skilled resources to improve upon or create reports and analysis for the most crucial decisions.
Consider the daily decisions made in your organization! Many of those decisions do NOT require 100% accurate data. Rather, they require agility and enough, solid data and analysis to see a trend or a pattern or spot an opportunity or a challenge. Users want to drill down and dive into data without having to ask for help from IT or an analyst. This agility will move your organization along with dependable data and prevent delays. Sharing this agile data environment and creating a social network of users to use, rate and comment on the data will allow for learning, sharing, collaboration and an increased understanding of interrelationships and dependencies within the enterprise.
By balancing high-quality (IT curated) data with ‘popular’ self-serve data preparation, in a social/sharing environment, your organization can 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. Sharing, rating, ranking, commenting and popularizing data will usher in the new generation of business intelligence analysis and make every market more competitive and successful.