Articles & Resources
Explore our articles and resources on data and analytics.
The Importance of Data Strategy in 2023
In 2023, companies need a data strategy more than ever as the landscape of data management and analysis continues to evolve and become increasingly more complex.
How to Build a Data Strategy Roadmap
A data strategy roadmap is a step-by-step guide to what needs to be done to achieve your desired business goals.
Data Strategy Assessment: Current and Future State Analysis
By performing a data strategy assessment, you can answer critical questions about the data’s current state and its future state development.
Enterprise Data Strategy: What is it? And why is it important?
Companies that utilize enterprise data strategy, are 58% more likely to surpass revenue goals when compared to non-data-driven competitors.
Scrum Master Best Practices to Accelerate Data Projects
Scrum is a Delivery Framework, under the Agile umbrella, that can accelerate initiatives, breakdown data silos, and bring organizations together as a team to progress any project. Individuals certified in Scrum are known as Scrum Masters.
Don't Let Technical Debt Bankrupt Your Data Foundation
Technical debt is commonly described as efforts deferred for the purpose of meeting deadlines or goals that will later need to be revisited and reworked for the final state product. It’s a tradeoff between gaining short-term benefits while sacrificing long-term value and overall efficiency.
Why do you need a Data Strategy now more than ever?
With increasing globalization and technology developments spurring modern economics, Data Strategy has been vital in identifying and understanding customers.
Data Offense or Data Defense: Flexibility vs Control
Data-driven organizations understand that their data is a strategic asset and to properly harness its power it must be supported by a sophisticated data strategy.
Implementing a Proof of Concept (POC) Approach
Many c-suite executives are perplexed at the amount of money their organizations spend implementing and integrating data and software applications with limited evidence that they will even align with desired business outcomes.