Please join me on March 30th at 11AM CDT for my first official post-retirement talk!
I will be chatting with Mike Lampa from Great Data Minds about my career and plans post-Snowflake. I expect we will cover a wide range of topics including what community and technical evangelism is all about, as well as what made me jump from nearly 30 years in the Oracle world to a small startup with less than 100 people that claimed to have re-invented data warehousing in the cloud.
LONDON, Feb. 16, 2022 /PRNewswire/ — DataOps.live, the London-based software company dedicated to helping organisations to build and manage their essential data applications and data products more effectively, is delighted to announce that Kent Graziano has joined its Advisory Board with immediate effect.
Could not resist staying out of the fray! I have worked with these folks from their earliest days as a Snowflake SI partner, and now as a software partner that supports the Snowflake Data Cloud. I am looking forward to helping Justin and Guy in the next stage of evolving the DataOps.live platform towards the vision of #TrueDataOps.
Shortly before leaving Snowflake last year, I was interviewed for this post about one of the worst case examples of data siloes I had seen – we called them data puddles!
A few years ago, Kent Graziano joined a big organization to work on its data. The first problem was that nobody really knew what and where all the data was. Graziano took his first three months on the job investigating data sources and targets, ultimately creating an enterprise data map to illustrate all the flows. It wasn’t pretty.
“In the end, I discovered that the same data was being sent to three or four places,” he said. In one case raw data was transformed and stored in a data warehouse, then moved from there into another warehouse—which was also pulling in the original raw data.
Graziano, who recently retired from his post as Chief Technical Evangelist at Snowflake, said this scenario is entirely common. Data scattered and copied in lakes, warehouses, data marts, SaaS platforms, spreadsheets, test systems, and more. That’s mass data fragmentation, or, more colloquially, data sprawl or data puddles.
Indeed, 75% of organizations do not have a complete architecture in place to manage an end-to-end set of data activities including integration, access, governance, and protection, according to IDC’s State of the CDO research, December 2021. This lack of governance combines with legacy systems, shadow IT, and good intentions to pave the road to a lot of fragmentation.
Check out the rest of the post to learn how data sprawl hurts businesses and what to do about it. Read it all here!
Last week I had the privilege of being interviewed by Nick Heudecker (former Gartner analyst and current Senior Director at Cribl) for the Data Mesh Learning Community. In our interview, we covered the idea of empowering business domains to really own and manage their data via things like templates and a center of excellence, not to just give them the responsibility of owning their data and leaving them to figure the rest out on their own. We also discussed the need for organizations to focus on investing in growing a data culture, not just investing in the newest cloud based tooling. Really, how do we lower the barriers to accessing, sharing, and leveraging data and get people to really think about data-as-a-product.
Like Agile before it, Data Mesh is as much about changing the way an organization thinks and works as it is about technology. I argue that the people and organization aspects of adopting a data mesh approach are more important than the technology aspects. Without the right approach, the best technology (like Snowflake), is not going to solve your organization’s data problems.
See the full interview here:
So what do you think about all this data mesh stuff?
The Data Warrior
P.S. For much more on the thoughts about #datamesh, check the other podcasts and videos listed on my Snowflake Resources page.
What a great event! So many announcements and great demos, plus and awesome live Q&A with our Snowflake leaders.
At Snowday 2021, Snowflake announced exciting new product capabilities that expand what is possible in the Data Cloud. In addition to announcing Python support in Snowpark (currently in private preview), these latest innovations make it easier for organizations to maintain business continuity across clouds and regions; help data engineers and data scientists build pipelines, ML workflows, and data applications faster; and remove the complexity of getting the right data into the hands of customers.
The Snowflake Data Cloud is a global network connecting organizations through data, creating new opportunities for collaboration to improve business outcomes, and fundamentally changing what is possible across industries. For Kraft Heinz, its data science teams are able to build and test models dramatically faster in Snowflake compared with its prior data lake. For NBCUniversal, it’s building brand-new advertising targeting and measurement products, in a secure and privacy-compliant way using Snowflake’s governance and data sharing capabilities. And for 84.51°, it’s built a Collaborative Cloud that takes complexity off the table and unlocks new possibilities for grocers and CPGs sharing and collaborating on data.
Snowflake continues to expand the scope and possibilities of the Data Cloud, delivering unique innovations that enable customers to: