If there's a recurring mistake I see, it's when someone shows me their data strategy, and it's only a pure data focus—whereas success is when you look at it holistically; it’s people, business and vision.
When it comes to building a data strategy there are five key blocks—Vision, Value, Governance, Organization Design, and Culture.
Enterprise data strategy should align with business goals to help ensure the needs of end-users are met. This should be continually monitored and improved upon across a range of areas in the business, including; people, processes, outcome alignment, technology and culture.
To implement a new data strategy in an earlier-stage business, try to weave and embed a data-first culture throughout all of the parts of the business that you can. The more people and processes a data strategy can affect, the more impactful it will be.
The people aspect of creating an effective data strategy is particularly important because people are harder to change than processes or technology. The way people think about and approach problems with data can be difficult to change, especially at scale, so more focus is needed to make sure that changes to align people with data are executed well and retained in the long term.
Top 10 Data Science Tools To Use in 2024
Abid Ali Awan
Google Cloud for Data Scientists: Harnessing Cloud Resources for Data Analysis
A Guide to Docker Certification: Exploring The Docker Certified Associate (DCA) Exam
Bash & zsh Shell Terminal Basics Cheat Sheet
Functional Programming vs Object-Oriented Programming in Data Analysis
A Comprehensive Introduction to Anomaly Detection