Dirty Jobs was a TV series on the Discovery Channel hosted by Mike Rowe performing the difficult, strange, disgusting, or messy parts of people's occupations. Every episode since it was first aired in 2005 has had exactly the same opening: My name's Mike Rowe, and this is my job. I explore the country looking for people who aren't afraid to get dirty ” hard-working men and … [Read more...] about The Dirty Job of Data Provisioning in Energy Utilities
Strategy
Learn everything about data strategy, what it should include in order to be successful, and how you can develop a data-driven business strategy for your business.
Propelling Utilities to a Digital Future
Back when I was working as a young system integrator there used to be a well-worn phrase rolled out by people in technology or software procurement "You'll never get fired for hiring IBM" I am sure you know it. If not, you're most probably a digital native and therefore never heard of the saying. Back in 1998, IBM was the biggest American tech company by revenue. IBM was so … [Read more...] about Propelling Utilities to a Digital Future
“Bad Choices make Great Stories” – Enterprise Architecture Blueprint for Utilities – Part 2
Bad Choices make Good Stories. There is a famous saying Bad choices make good stories . What might be true in life, seems wrong for utilities' IT or enterprise architecture. Part 1 of our Enterprise Architecture Blueprint for Utilities “ The Good, the Bad and the Ugly , discusses how bad decisions lead to huge technical debt, an Accidental IT or bad architecture. In part 2 of … [Read more...] about “Bad Choices make Great Stories” – Enterprise Architecture Blueprint for Utilities – Part 2
Enterprise Architecture Blueprint for Utilities Part 1
The Good, The Bad and the Ugly Some days ago, I was co-hosting a webinar on Piecing together the Enterprise Architecture Puzzle for Utilities . During our virtual roundtable, our guests including Klaus Wagner, (Enterprise Architect, Netze-BW / EnBW) and Rinse Veltmann (Director Solutions, Energyworx) discussed an enterprise architecture blueprint for the Utility 4.0 future and … [Read more...] about Enterprise Architecture Blueprint for Utilities Part 1
Data Analytics Assesses Event Impacts on Developing Economies
Countless experts have discussed the proliferation of big data over the last decade. The global market for big data is projected to reach $229 billion within the next five years. This is an important testament to the incredible value that big data has brought to organizations around the world. Despite the global impact of big data, the focus is too frequently viewed through the … [Read more...] about Data Analytics Assesses Event Impacts on Developing Economies
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What is data strategy?
Data strategy, also called analytics strategy or business data strategy, is the organizing principle for an enterprise’s investments in data and data-related technologies. Data strategy provides a framework for thinking through the complex trade-offs in managing data as an enterprise resource.
It helps business leaders make decisions about where to focus their data investments and how to maximize the value of those investments. Want to learn more about data strategy? Datafloq has courses available. Contact us to get started.
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How does data strategy work?
Data strategy starts with a clear understanding of an organization’s business goals. From there, it defines the role that data will play in achieving those goals and outlines a plan for how to get the most value from data. Data strategy is an essential part of any organization’s overall data business strategy.
When done well, it can help organizations make better use of their data and gain a competitive edge. But when executed poorly, it can lead to wasted resources and missed opportunities. Data strategy is not a one-time exercise; it should be revisited regularly as an organization’s business goals and needs evolve.
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What are the four big data strategies?
Big data can be a big help when it comes to making decisions for your business. But how do you make sense of all the data out there? One way is to use the four big data strategies:
- Performance management — Helps you track and improve your business’s performance.
- Data exploration — Helps you understand your data and find hidden patterns.
- Social analytics — Helps you analyze data to understand customer behavior.
- Decision science — Helps you use data to make better decisions.
These strategies can help you get the most out of your data and make better decisions for your business.
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What should a data strategy include?
A data strategy should be designed to help an organization achieve its business goals. It should be aligned with the organization’s overall data business strategy to be effective, considering its unique needs, such as its size, industry, and geographic location.
The data strategy should also define the roles and responsibilities of those responsible for managing the data. Finally, the data strategy should identify the tools and technologies that will be used to collect, store, and analyze the data. By considering these factors, an organization can develop a data strategy to help it meet its business goals.
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What is a big data strategy, and why should companies have the strategy in place?
Big data refers to a large number of data companies have access to. It can come from various sources, including social media, transaction records, and sensors. The challenge for companies is to make sense of this data and use it to improve their business.
A big data strategy helps companies to set goals and priorities for dealing with big data. It also helps them to invest in the right technologies and build the necessary expertise. Companies will struggle to get the most out of their data assets without a big data strategy. They will also be at a competitive disadvantage compared to those companies that have invested in big data.
