Microsoft recently shared what I think is a pretty useful whitepaper on how to approach Data Marts and BI Solutions.
Recently I decided to move from AWS to Azure for the hosting of my “Sandbox” sites. With the move, I plan to add serve up live interactive data content highlighting different “data” projects of personal and professional interest.
Much of what I’ve worked on is contained on “corporate” portals and intranets. The move to Azure from AWS for “server based” content will allow more flexibility and access to Power BI, SharePoint and Microsoft Teams.
A took a quick look at the COVID-19 data using Power BI and Qlik Sense. Both have their advantages – but are using the same dataset. A shared table in Snowflake (CT_US_COVID_TESTS).
Yesterday I attended a free workshop put on by Snowflake. The session entitled “Zero to Snowflake in 90 Minutes” provided information on Snowflake’s Architecture, Performance and Scalability as well as a “hands-on” demo. Snowflake touts itself as “The Data Warehouse Built for the Cloud” and is gaining enterprise customers at a dizzying pace.
The “demo” used data from Citi Bike – New York City’s bike share system. Citi Bike is the nations largest bike sharing service. The data can be downloaded from: https://www.citibikenyc.com/system-data
The workshop provides an introduction to how to setup and use Snowflake. The outline is below and the lab takes 90~ minutes:
Module 1: Prepare Your Lab Environment
Module 2: The Snowflake User Interface & Lab “Story”
Module 3: Preparing to Load Data
Module 4: Loading Data
Module 5: Analytical Queries, Results Cache, Cloning
Module 6: Working With Semi-Structured Data, Views, JOIN
Module 7: Using Time Travel
Module 8: Roles Based Access Controls and Account Admin
Module 9: Data Sharing
I found the workshop very interesting and for two reasons. First, it covered all the basics of using a cloud based database. Users loaded data from a S3 bucket, parsing both csv and json files. Queried the database and managed schema’s and security. The second reason why enjoyed the session is because Qlik’s Elif Tutuk used this dataset for a Qlik Sense Demo app.
I found a copy of the old Qlik Demo app and set it up on a Qlik Sense instance.
I created a ODBC connection (using a DSN) and was able to update the data from Snowflake. The combination of Qlik Sense and Snowflake is compelling. I liked the Snowflake demo especially when I could match it up with the visualizations from Qlik Sense.
This graphic breaks down the a number of key terms and concepts often used interchangeably.
Thanks for stopping by EricFrayer.com. Over the years, I’ve used wiki’s, blogs and other content sharing tools to post thoughts, tips and reference materials. Most of this was internal to the companies I’ve worked for. Either on “SharePoint Intranets” or “Confluence” pages or other web based knowledge management or content sharing sites.
At this point, it makes sense to post “samples of work” to build out my professional online resume. I’m using AWS and Azure to host this content. My interest is in finding insights and making data actionable. Not just buzzwords but actually demonstrating how all the pieces come together to give the end-user meaningful analytics.
I’ve been thinking about this for 10 plus years. Now it’s time to share!
For a number of years I thought Business Intelligence needed people who could “span” both technologies and business understanding. The most valuable BI professionally have both technical knowledge and domain data understanding.
I setup this Sandbox in May 2018. I was researching how much effort is needed to use AWS Lightsale vs WordPress hosted sites.