“Kaycee was awesome to work with - by far my favorite sales person I've ever worked with. Kaycee is passionate about his work, knows how to read his customers, creates a time line that everyone signs onto, works multiple verticals at a customer in parallel such as licensing, legal, procurement, as well as keeping his eye on the "main" players. Kaycee was a powerhouse at Delphix and was the go to man who brought home every deal when one of the other sales people had come to a dead end. I wish I had a chance to spend more time with Kaycee both to learn and for the sheer fun of it.”
About
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What are the top data lake design practices for BI?
The challenge we face when talking about self-service access & discovery is that there is first a need to pull and extract data from where they natively reside to move it into a Data Lake before any value can be obtained. The time spent on the manual effort, on the data movement and on the cost of compute to transform the data BEFORE it can even been seen is long, complex, and expensive. There's NOTHING self-service about it. The legacy way of doing data management or the "modern" data stack must change. True "self-service" means 1 person and just 1 person can discover, access, build and consume data without involving an entire time to use a myriad of tools. This means that the data must be fresh. This is the new bar that we must meet.
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What are the top data lake design practices for BI?
Agreed. We are sometimes “trapped” by what we used to do and by what has “always been done this way” syndrome. Sometimes we forget that a methodology came about to address both the problems and available technologies at the time. But technology advances and problem change. So by right, it makes no sense to keep the process the same. It makes no sense but it is easy and comfortable to not change our way of thinking or to learn new approaches. Changing technology and products is easy. Changing human behavior is always much harder.
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What are the most important considerations when designing a hybrid schema for business intelligence?
Agility: A) It's not just easier to adjust but it's also much easier to set up. Notions like a Fact table vs a Dimension table no long need to be set in stone. B) Use cases that require tables to be joined from different sources and vendors can be achieved. Considerations: A) Data can be more "scattered" as it it's less structured. This may make discovery more difficult, so make sure there's a strong metdata and search layer to enable not only easy but fast / robust discovery. B) Query data across multiple / different data sources will require a data virtualization layer. C) Datasets & queries may be much bigger than traditional schemas so ensure there's a way to automatically scale up in performance and scale down to control costs.
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How can you ensure data accuracy without sacrificing speed in BI reporting?
We’ve fallen victim to one paradigm that is outdated and no longer relevant with modern times. This is the existing process of going through so many steps to build a report without knowing how long, frequent or useful it will be. Most will be used once as they serve their purpose. So why do we insist on applying the same process to all reports when not all of them have equal value ? We shouldn’t. Reports should be treated as data products and the time to consume should be a critical factor. If I need a report to make a dry decision in the next 30 minutes but I may not use that report again, then why should that have the same process as my monthly accounting report? It’s time to adapt.
Activity
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A conversation with the one and only Aaron Belinfanti (AB) at Cisco TechBeat.
A conversation with the one and only Aaron Belinfanti (AB) at Cisco TechBeat.
Liked by Kaycee Lai
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I am so proud to watch my kids step into leadership roles in the technology space. A summer camp through the BOYS AND GIRLS CLUB OF MIDDLE TENNESSEE…
I am so proud to watch my kids step into leadership roles in the technology space. A summer camp through the BOYS AND GIRLS CLUB OF MIDDLE TENNESSEE…
Liked by Kaycee Lai
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I have just returned from London after celebrating my son Regan Lee’s graduation from Brunel University London! So proud of his accomplishments, 2…
I have just returned from London after celebrating my son Regan Lee’s graduation from Brunel University London! So proud of his accomplishments, 2…
Liked by Kaycee Lai
Experience & Education
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English
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Chinese
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5 people have recommended Kaycee
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Another summary of the power of #activemetadata utilization. At #Gartner we coined the terminology way back in 2012. It was primarily focused in the…
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Glad to be part of a Data community (with this Practitioner certification) that values continuous learning and structured development in Data…
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