Big Data in Utilities – Thematic Research

Big data analytics has the potential to address and improve several issues in the power sector – operational, strategic, and financial, among others.

Cloud computing, machine learning, Internet of Things (IoT), robotics, blockchain and cybersecurity are being deployed by utilities in their operations. These are the big current and future investment avenues for utilities, and they all have one thing in common: they generate huge amount of data. And the data generated is growing each year as more and more smart devices and technologies are being deployed within the power systems infrastructure by utilities as well as consumers. Much of the utilities’ infrastructure is becoming smart – meaning that it has built-in processing, connectivity, and sensing capabilities. Electric vehicles (EVs), smart home systems, grid management systems, and many more subsystems are likely to interface with utilities and provide them with potentially valuable data.

The challenge for utilities is to make this data useful and generate actionable insights from it. Benefiting from big data is not straightforward and utilities need to deploy a range of new IT solutions that allow them to collect the data in consistent ways, transport it, secure it, analyze it and store it. Solutions that manage big data in the industry need to quickly make sense of data from multiple sources and in diverse formats. Several big data analytics products and platforms are already being used in order to harness this data.

Currently only a small number of utilities have adopted big data analytics actively. It is mostly the largest utilities in the world and very few smaller utilities that have embraced the technology. While some of these utilities have designated other companies to implement big data in their businesses, some have collaborated with technology companies through partnerships and joint ventures to build new products and services specific to the power sector that can be sold to other utilities.


This report explores the usage of Big Data and analytics in the utilities industry.

The report discusses the latest trends and developments in the field of big data and how these affect utilities. The report further gives a brief analysis of the big data industry and lists several use cases and case studies for big data in utilities.

The report also explores the value chain of the big data industry and lists the companies implementing big data applications in the utility sector.

Reasons to buy

The report provides:

A comprehensive analysis of the present scenario and emerging market trends in the global big data industry.

Insights of the global market leaders and challengers in the big data industry and where do they fit in the value chain.

Extensive analysis of the applications of big data in power utilities.

Profiles of major market players within the big data industry, which aid in interpreting the competitive outlook of the big data industry.

Companies mentioned

Duke Energy, Enel, EDF, National Grid, E.On, Exelon, SGCC, TEPCO, KEPCO, Innogy, Vattenfall

Table of Contents




Data trends 7

Technology trends 8

Data center trends 11

Macroeconomic trends 12

Regulatory trends 12

Utility trends 13


Growth in big data is being driven by the increased use of broadband internet among several other factors 14

Big Data and IoT in Utilities 15

Mergers and acquisitions 15

Timeline 17


Predictive Maintenance 19

Data driven consumption management 19

Optimization of V2G systems based on EV charging, parking, and retail consumption data 19

Dynamic Line Rating 19


Vestas using IBM’s big data software and hardware to pinpoint ideal coordinates for wind turbines within a farm 20

Enel uses GE’s Predix platform to draw insights from big data analytics 20

Southern Company and Schneider’s Prism technology 20

ROMEO project to use big data and AI to reduce offshore wind O&M costs 20


Big data generation 21

Big data management 21

Data governance and security 22

Business intelligence 22

Data analysis 22

Data storage 23

Data processing 23

Data aggregation 24

Data integration 24

Big data product development 24

Big data consumption 24


Public companies 25

Private companies 31

Utilities implementing big data 33




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