ANALYTICS 3.0 DAVENPORT (2013)

ANALYTICS 3.0 DAVENPORT (2013)

1. ANALYTICS 1.0 ERA OF "BUSINESS INTELLIGENCE"

   • For the fisrt time, data about production processes, sales, customer interactions, and more were recorded, aggregated, and analyzed. It was a time of progress in gaining an objective , deep understanding and beyond intuition when making decisions.

2. ANALYTICS 2.0 THE ERA OF BIG DATA

   • It was internally and externally sourced as well, coming from the internet, sensors of various types, public data initiatives such as the human genome project, and captures of audio and video recordings. Companies rushed to biuld new capabilities and acquire customers. The broad recognition of the advantage a first mover could gain led to an impressive level of hype. They attracted viewers the their websites through better search algorithms, recommendations from friends and colleagues, suggestions for products to buy, and highly targeted ads, all driven by analytics rooted in enormous amounts of data.

3. ANALYTICS 3.0 ERA OG DATA-ENRICHED OFFERINGS

   • If your company makes things, moves things, consumes things or works with customers, you have increasing amounts of data on those activities. Every device, shipment, and customer leaves a trail, you have the ability to analyze those sets of data for the benefit of consumers and markets.

4. THE NEXT BIG THING, IN DATA

   • Today it focuses primarily on energy managment, including energy optimization, smart-grid managment and building automation. It makes use of data and analytics to provide so-called intelligent customer offerings,. These include intelligent fleet management, intelligent vehicle-charging infrastructures, intelligent enegry management, intelligent video security analysis, and many more. (INTERNET OF THINGS).

5. CREATING VALUE IN THE DATA ECONOMY

   • One thing is clear, the new capabilities required of both long-established and start-up firms can't be developed using old models for how analytics supported the business. The big data model was a huge step forward , but it will not provide advantage for much longer.

6. TEN REQUIREMENTS FOR CAPITALIZING ON ANALYTICS 3.0

   • 1.- MULTIPLE TYPES OF DATA, OFTEN COMBINED 2.- A NEW SET OF DATA MANAGEMENT OPTIONS 3.- FASTER TECHNOLOGIES AND METHODS OF ANALYSIS 4.- EMBEDDEDA ANALYTICS 5.- DATA DISCOVERY 6.- CROSS-DISCIPLINARY DATA TEAMS 7.- CHIEF ANALYTICS OFFICERS 8.- PRESCRIPTIVE ANALYTICS 9.- ANALYTICS AT AN INDUSTRIAL SCALE 10.- NEW WAYS OF DECIDING AND MANAGING 10.-

7. ALEXIS SANTANA - 12284