Analytics - Analysis of data

Analytics - Analysis of data

1. History

   • 1950: Field of business analytics.
     • Capture a larger quantity of information and discern patterns quickly.
     • Analytics 1.0
       • Enterprise data warehouse and business intelligence software.
   • Use of data to decision making.
   • 2000: Analytics 2.0
     • Internet-based and social network firms with new kinds of information.
   • Analytics 3.0
     • Big data firms in Silicon Valley began investing in analytics to support customer-facing.

2. Analytics 1.0

   • Facts replace intuition.
   • Manage data.
   • Competing on analytics.

3. Analytics 2.0

   • Externally sourced.
     • Databases: NoSQL.
     • Hadoop clusters.
   • Sensors.
   • Public data.
   • Audio and video recordings.
   • “In memory” and “in database” analytics.

4. Analytics 3.0

   • Information of every company can be analyzed.
   • Data-enriched offerings.
     • more-valuable products and services.
       • Companies must ask how the analysis of data can create value for themselves and their customers in the new data economy also need new approaches to decision making and management.
         • Head Principal ideas Secondary ideas Close
   • New conversions to data and analytics offerings.
   • Shortcuts to decisions and actions.
   • data processing and analysis are related into operational and decision processes
   • Types of analytics:
     • descriptive: past.
     • Predictive: Based on past to predict.
     • Prescriptive: models to specify optimal behaviors and actions
   • Chief analytics officer.

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