4 min read

MDS Newsletter #34

MDS Newsletter #34

Hey folks!

We hope you had an awesome start to this week because we sure did! MDS Twitter has now 3000+ followers🎉. Keep following MDS because we have a lot more exciting things coming up super soon!

  • GoodData is a composable data and analytics platform that gives customers the flexibility to build and scale any of their data use cases - from self-service and embeddable analytics to machine learning and IoT.

    GoodData has raised a total of $167.7M in funding over 13 rounds. Their latest funding was raised on Jul 27, 2021, from a Debt Financing round.
  • DataKitchen is an enterprise DataOps Platform that simplifies complex toolchains, environments, and teams. It automates end-to-end data workflows so cross-functional teams can quickly innovate, test, and deliver error-free and on-demand insight.

    Headquartered in Cambridge, MA, DataKitchen was founded in 2013

E-commerce is one of the fastest-growing industries and generates an enormous amount of data. Learn from the data stack of Catch, Australia's biggest online shopping platform, how the e-commerce industry is building its data stack.

Have a look at what data tools Catch.com.au is using here

Good reads and resources

  • The Future of Data Catalogs: The data catalogs were built to be passive, they brought metadata from a bunch of different tools into another tool. Read this article by Prukalpa where she talks about the problems with this approach and how active metadata can solve them and make intelligent data dream a reality. She discussed various use-cases of active metadata and how we can go beyond data catalog in the future.
  • The Definitive Guide to Decision Intelligence: Businesses today have massive amounts of data and increasingly complex business decisions to solve for this data, but lack insights to bridge data to decisions. The analytical output doesn’t scale with data volumes because today’s tools, processes, and teams are siloed along the lines of descriptive, diagnostic, and predictive analytics, with time-consuming handoffs and insights gaps. Decision Intelligence offers a way to bridge these insights gaps, helping users make better, faster, insight-driven decisions at the cloud-scale — with continuous improvement. Download this E-book by team Tellius to learn more about Decision Intelligence.
  • How to Build Your Own "PLG CRM" (Part 1): Team Pace, in a 4-part series of ‘How to Build Your Own "PLG CRM"’ has discussed how you can build a basic "PLG CRM" using free or low-cost tooling. Whether you choose to build your own or work with a dedicated platform, there are many new and interesting workflows you can enable by enhancing your existing CRM with data from your SaaS product.

Community Speaks

This week's question: What are the gaps that the modern data stack promised to solve but is still unable to do so?

You can send answers by replying to the email or writing to us at [email protected]

Last week's question: Can someone explain to a 5yo what's the difference between data lake, data warehouse, and data lakehouse?

Data Warehouse: Central repository of data on which you can create business
-When you should use it: Use it when you have structure data only and you want to create Dashboards, reporting, etc. on top of that.
-Don't Use: Don't use if you have unstructured data (There are many other reasons but to keep it short and crisp)
Data Lake: Term introduced after Hadoop became open source in 2008.
-Repository for every kind of data - structure, semi-structured, unstructured.
-Bring all data under one hood (i.e. data lake) and then process it forward depending upon different use cases. All the cleaning and organization happens here only with the help of different tools and architecture.
Problems: Data updates and deletes are not easy tasks.-Amateur Data Governance and Data Security.
data lakehouse - DataLake + Data Warehouse = Data Lakehouse
-It has solved the shortcomings of both platforms.
-It handles Unstructured and semi-structured data as well.
-It provides ACID transactions as well( deletes and updates)
-Standard storage formats are there which are fast and effective
by Mayank Malhotra , Data Engineering Consultant at Accenture AI

Read more such insightful answers by Vladyslav Hrytsenko and Shane Gibson over here

Upcoming events and webinars

  • The CEO of databricks, dbt labs, and Fivetran will participate in an online event "The Future of the Modern Data Stack" hosted by TechCrunch on May 24, 2022.
    Register here
  • Delphix is organizing the "Data Company Summit 2022" in New York on May 25, 2022.
    Register here
  • TigerGraph is hosting a virtual event  "Graph + AI Summit" from May 24-26, 2022.
    Register here

MDS Jobs

  • Sprout Social is hiring a 'Senior Manager, Data Engineering'
    Location - US
    Data Stack- Airflow, dbt, Redshift, Tableau, Meltano, Amundsen
    Apply here
  • Webflow is hiring a 'Senior Analytics Engineer'
    Location- US, Remote
    Data Stack- Stitch, dbt, Snowflake, Tableau, Census
    Apply here
  • Gladly is hiring a 'Senior Data Engineer'
    Location- US
    Data Stack- dbt, Snowflake, Looker
    Apply here

    Are you hiring for data roles? Let us know and we will add it to next week's edition.

🔥 on Twitter

Just for fun😉

Subscribe to the MDS Newsletter now and get all the latest happening from the data space right in your inbox each week! I promise, soon you'll outsmart every other data nerd😉

If you have any suggestions, want us to feature an article, or list a data engineering job, hit us up! We would love to include it in our next edition😎

About Moderndatastack.xyz‌‌ - We're building a platform to bring together people in the data community to learn everything about building and operating a Modern Data Stack. It's pretty cool - do check it out :)