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Analytics 3.0 is stage of maturity combines of best of Analytics 1.0 which is Traditional Analytic and Analytics 2.0 which is Big Data. This term (Analytics 3.0) is not quite popular in industry, but this involves analytics at speed and scale.

Era of Analytics

Era of Analytics Explained –

Analytics 1.0 typically refer to conventional Business intelligence which includes Enterprise Reporting and dashboarding which are totally based on past data and giving clear picture to Organization that how they were performing. So phase typically talks about descriptive analytics.

Analytics 2.0 typically refer emergence of big data. In this era, Organizations deals with this Big data along with adaption of data mining, predictive and advanced statistical techniques. It also involved analysis of historical data to make future prediction, identify pattern in data which helpful to in decision making.


In Analytics 3.0, containing several key developments which mentioned as below -

  1. Big Data: Handling and analysing huge volume of data (structure and Unstructured) this also included sensor’s data, social media produced data.


  1. Real-Time Analytics: Analytic 3.0 focuses on processing real time or near real time data to Organization so that there would be no delay in taking business decision based on data.


  1. Advanced Analytics Techniques: Analytics 3.0 focuses, use of advanced analytics techniques such as Data mining, ML (machine learning), Pattern matching, forecasting, cluster analysis, NLP (Natural Language Processing), neural networks. Using these organizations able to have more insights to their data for different types of analysis like predictive and prescriptive.


  1. Self-Service Analytics: Analytics 3.0 focuses on self-service analytics so that business user does not depends on IT people for analytics they are directly access tool/technique to build their own analytics. So, these tools provide very keen interface along with drag and drop functionalities which help business user to create their own dashboards/report and analysis.

How SAP Analytics - helping organization in above area to have benefits of Analytics 3.0 -

  1. Big Data Analytics: SAP offering this Big data capabilities to their customer by providing tools called SAP HANA and SAP Data Intelligence. Using these tools customer gather and analyse huge amount (TeraBytes) of data and making better business decisions. SAP Datasphere (SAP Data Warehouse Cloud) – This is SAP's cloud-based data warehousing solution for organizations. This solution is SaaS based provides organization a platform to perform data integration, deployments, reporting and analytics also provides BI functionality connect to SAP and non-SAP data sources and tools.


  1. Real-Time Analytics: Using SAP HANA enables organizations to process and analyse data in real-time and enabling timely decision-making. SAP Analytics cloud is SaaS based solution provides organizations to access and analyse data in real time along with better visualization for decision making.


  1. Advanced Analytics : SAP’s Predictive analytics allows organizations to build predictive model (Regression, Cluster analysis) to perform advanced analytics.


  1. Self-Service Analytics: SAP provides features of Self-service analytics using SAP analytics cloud (SAC), this enabled business user to analyse and visualize data without any IT help. SAC offer intuitive user interface to Business user to create their own dashboard and reports independently.

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