BI tools landscape

Generation 1: It is the central guardian. • BI tools are code —> Need SQL to run queries. • Everyone depends on the IT team to run queries • The IT provides a static report which can take days to product The features by which this era is defined • Query in: SQL, python, …. • Static reports The issue with this era This era is problematic because the data team is a HUGE bottleneck. Generation 2: The birth of self-service A more agile approach replaced the first one: an approach that fostered self-service capabilities. • New BI tools eliminate the tech stack. Focus: provide data discovery and visualization tools to business users. • Now business users can access the data and play with it. The can now conduct ad hoc analysis of multiple data sources. • Data visualization allows for modern BI to be as much an art as a science. The key performance indicators become more accessible to employees, their bosses, and their companies as a whole. As a result, IT-centric BI vendors quickly started to build these data discovery and visualization capabilities into their product portfolios. • There is still a dependence on the data team for data preparation and modeling • Reporting/KPI’s focused. Generation 3: Business users empowered. —> Augmented analytics. • promises to reduce the dependence of business users on the data team. • Today, many well-known BI platforms have built-in capabilities to automate data preparation and detect some correlations and anomalies in large data sets. Some platforms are capable of analysis and even insight generation and action plan generation, but there is still a considerable amount of hype to muddy the waters. • Business users don’t require IT assistance to define data models • Data preparation and analysis aided by artificial intelligence • Ease-of-use greatly increased by AI automation • Data correlation and insights automatically generated to drive decision-making Feature definitions: Business focus/ Analyst focus: Tools for analysts’ code are needed to create and generate reports but business users can refresh them. You need to be a SQL pro to truly get value out of the tool. When we put both: business teams across the organization with a data analytics team to support/ No code interface: With a drag-and-drop interface to create powerful, in-depth analyses or simple dashboards + the user can connect, query and visualize your data without writing code. Data exploration: Explore the underlying query of every chart without breaking the actual dashboard. Allow non tech user to answer more complex questions. Dashboard builder:build a dashboards that suits our needs: your brand color, etc… Drill down: Click on a chart to have access to the underlying data of which records are at play to describe your metric. Metric layer: