Skip to main content
HomeBlogLife at DataCamp

Why Data Science Readiness is Important for Any Industry

Learn why data science readiness should become a priority in your company if it isn't already.
Jul 2019  · 4 min read

Organizational Readiness for Data Science

Data science readiness is important for every organization—no matter if you’re in an industry that is traditionally associated with data science and analytics or not. KDnuggets summarizes the four components of organizational readiness as strategic, domain, cultural, and operational readiness.

Defining Data Science Readiness

Organizations must thoughtfully incorporate these four elements when preparing for data science initiatives. Strategic readiness helps companies make the business case to link data science to organizational priorities and get executive sponsorship. Domain readiness is about investing in infrastructure, namely the tools and skills required to easily access and analyze data. Cultural readiness establishes the conditions for every employee to learn to speak the language of data and drive better data-driven results. And operational readiness enables the execution and optimization of data science functions with proper planning. Companies must be mindful of their unique data needs and ensure early fit in all these areas to position themselves for success.

The Data Science Hierarchy of Needs

AI is hot and many companies want to jump right into it. But you have to walk before you can run, and before you can systematize AI, you must have the readiness level to do so. This is what building a data foundation is all about. Monica Rogati’s Data Science Hierarchy of Needs is a practical way to approach data science readiness.

Data-Driven Energy Consumption with Smart Meters

Sometimes, organizations may not be actively looking to prepare for data science but are forced to do so to meet external demands. Let’s look at an example with utility companies in the UK, where the government has mandated the installation of smart meters in every home and small business by the end of 2020. The government cites adapting to modern data needs and consumer concerns as the reason for the initiative in their 2018 progress report: they believe smart meters will help customers use energy efficiently and save on energy bills by giving them more visibility into their actual consumption.

Data Science Insights Into IoT

Smart meters are part of a fast-growing field called the Internet of Things (IoT), which is often combined with data science. IoT refers to gadgets that are not standard computers but still have the ability to transmit data. Data science can provide great insight into the information gleaned from IoT. For the UK smart meter program to be successful, smart meters must be able to transmit data, determine energy consumption patterns, and inform the user how they can make changes to conserve energy.

How Utility Companies are Adopting Data Science

Utility companies in the UK are scrambling to meet the 2020 deadline, and there are a lot of moving parts. Strategically, they must get executive sponsorship for investment in analytics support to track their progress. They must have domain readiness to monitor the progress of the smart meter program against targets, which requires monitoring installations and costs and ensuring operability. They must ensure cultural readiness for everyone at the company—from executives to installers—to understand product-market fit and IoT capabilities of the smart meters. Finally, there must be operational readiness to quantify the impact of smart meter installation on energy consumption and cost—and to determine whether smart meters are really worth the hype.

If you’d like to dive into practical applications of data science for IoT, take our course on analyzing IoT data. We walk you through exactly how to access IoT data, process it, analyze it for trends and outliers, and use it to build a machine learning pipeline for real-time predictions.

If you’re a business leader interested in organizational readiness for data science and analytics, learn more at datacamp.com/business. Click here to schedule a demo of our platform.

Topics
Related

DataCamp Instructor Connect Summit: February 15-16, 2023

Have you ever considered sharing your data skills? Learn about how you can at the DataCamp Instructor Connect Summit.
DataCamp Team's photo

DataCamp Team

2 min

The Environmental Impact of Digital Technologies and Data

Our increasingly digital lives come with a cost. This article analyzes the implications of digital technology and data for the environment.
Javier Canales Luna's photo

Javier Canales Luna

19 min

Excitement for DataCamp’s Radar 2023 Event Intensifies

Find out more details about this year’s Radar event, including what’s on the agenda, who’s speaking, and what you can expect during the event.
Matt Crabtree's photo

Matt Crabtree

3 min

Year In Data 2023: Celebrating Your Data Journey

Year In Data 2023 is a new experience for DataCamp users that honors your dedication throughout a year of learning. Join us in celebrating and sharing your achievements with the world.
Luigi D'Introno's photo

Luigi D'Introno

3 min

Avoiding Burnout for Data Professionals with Jen Fisher, Human Sustainability Leader at Deloitte

Jen and Adel cover Jen’s own personal experience with burnout, the role of a Chief Wellbeing Officer, the impact of work on our overall well-being, the patterns that lead to burnout, the future of human sustainability in the workplace and much more.
Adel Nehme's photo

Adel Nehme

44 min

Becoming Remarkable with Guy Kawasaki, Author and Chief Evangelist at Canva

Richie and Guy explore the concept of being remarkable, growth, grit and grace, the importance of experiential learning, imposter syndrome, finding your passion, how to network and find remarkable people, measuring success through benevolent impact and much more. 
Richie Cotton's photo

Richie Cotton

55 min

See MoreSee More