Linking Projects to Strategy
It can be challenging when stakeholders cannot translate business questions into technical requirements or do not provide enough context for data teams to do so. From there, the data team is often left to maintain the status of a series of ad hoc projects rather than connect these business questions to a larger more defined data strategy.
Back to Basics: Selling the Benefits of Data Projects
Data teams should be regarded as intentional business partners because they provide the underlying technology that enables business strategy and maintain data as a corporate asset. They can help educate business partners on the upstream and downstream impacts of poor data quality and they can help cultivate more effective ambassadors for data governance across the organization.
Finding Meaning in Data Projects by Asking: WHY
Most data teams cover WHAT and HOW with standard reports and KPIs. They will optimize processes and analyze business domains that will impact the company's bottom line from a data perspective. But how many data teams truly understand the WHY behind the reports they generate? How many actively consult with the business as a true partner to understand the underlying business concerns behind the numbers? Without the WHY, delivering true value in the WHAT and HOW is ten times harder.
The Importance of Scope
In driving data projects, I find people underestimate the impact of scoping projects effectively. Too often, you see technology leads with new platforms or tools looking for a problem to solve, or business leads with a unique one-off request from an executive reporting forum carry over to a data team as a priority requirement, whether it is or not.
Data Consumers Must Be Mechanics & Pilots: 5 Takeaways from the Guide
As data consumers, we need to be both mechanics and pilots. We must know how to gather, cleanse, and prep—and present data, make data-driven decisions, and influence data. That is a very broad set of skills.
Dos and Donts for Analysts Relying on ChatGBT
Data analytics is filled with complexity. Anyone saying otherwise is selling products. Knowing the data sources, data sets, general lineage, and behavior of the numbers are table stakes for the average data consumer. We must know where our data comes from. Much like we need to know where our food comes from and how it's processed. Is it safe to consume?