September 28 & 29, 2020 | Virtual
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In her interview linked above, Anita Fernqvist says one of her big challenges "is getting people to understand why data matters and why it should be central to every plan."
"Getting the data architecture right at the start saves time and money and improves delivery in the long run. Rather than order taking or dictating, I have to work together with the business to define the strategic plan. And my team and I have to execute impeccably to prove that we do what we say we will and earn the trust of the business."
I believe most enterprises will state that their data landscape is strategically designed/leveraged in their organization. Saying anything else would invite unwelcome oversight and create concerns for their vendors, business partners, and customers.
In reality - though, the data landscape of most enterprises are disparate and lack strategic alignment/direction due to acquisitional mayhem, stagnation of legacy systems, new systems development, and the like. Eventually - and with lots of effort, a data warehouse solution gets deployed that works around these issues and the business finally gets the strategic business and operational knowledge they need, but the core data architecture issues persist.
The quote from Anita, “Getting the data architecture right at the start saves time and money and improves delivery in the long run,” Is right on. However, I think it would take a CDO (Chief Data Officer) like position to drive such a transformative initiative forward, as “Data Architecture and Governance” affects just about everything in an enterprise. Let’s hope the CDO trend continues!
I'm hearing that a related challenge in data analysis is the role of TRANSLATOR to connect all the analytics with real business value. AI has changed the game, and data scientists are in high demand, but we need people who can see both sides of the data fence. And maybe that's part of "getting the architecture right" — lower or removing the fence all together...
Great. THank you for sharing
I love the hybrid approach used by Ms. Ferbqvist. It offers the best of both worlds: iterative, incremental development with a milestone-approach for status report.
Just as well I finally passed my mandatory training today on data management, left to wonder who is our local CDO was - but none so far! An interesting interview thank you for sharing Aaron!
Features of the Research and Development Project Plan:
1. Elasticity and adjustability.
That is, according to the predicted changes and implementation of the differences in the process, timely adjustments.
Give full play to the imagination and abstract thinking ability, form an integrated network to meet the needs of research and development project development.
Explore the internal and external factors of the research and development project, identify uncertainties and analyze the causes of uncertainty.
Can identify problems in a timely manner, provide a variety of operational solutions to the revision plan. It is worth noting that, as two written results at the end of the preparation of the research and development project, the research and development project plan is a core part of the research and development project plan, while the support plan is to serve the core content.
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