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Though you may encounter the terms “datascience” and “dataanalytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, dataanalytics is the act of examining datasets to extract value and find answers to specific questions.
The potential use cases for BI extend beyond the typical business performance metrics of improved sales and reduced costs. Business intelligence vs. business analytics Business analytics and BI serve similar purposes and are often used as interchangeable terms, but BI should be considered a subset of business analytics.
BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptiveanalytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was.
Co-chair Paco Nathan provides highlights of Rev 2 , a datascience leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “datascience leaders and their teams come to learn from each other.” If you lead a datascience team/org, DM me and I’ll send you an invite to data-head.slack.com ”.
IBM is using the power of its Watson Studio platform to extend the power of AI to people who fall outside the realm of datascience, machine learning and AI experts. IBM Watson Studio is an end-to-end analytics solution to help you gain insights from your data. The next step is to analyze the data.
What are the metrics that business wants to see and why it is valuable? Then we discover other metrics we can create to provide value along the line based on gathered requirements and interviewing right people and understanding business. Sounds like data scientists have to be great communicators. The data scientist does this.
Descriptiveanalytics: Where most organizations begin and linger Descriptiveanalytics answers the question: What happened? These are your standard reports and dashboard visualizations of historical data showing sales last quarter, NPS trends, operational thoughts or marketing campaign performance.
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