4 min read

MDS Newsletter #67

MDS Newsletter #67

"Happy New Year, dear readers! 🎉" As we celebrate the start of a new year, we want to thank you for your support and engagement in the past year. Your love and enthusiasm for data have truly made it an amazing year for us.

As we look ahead to 2023, we are excited to bring you the freshest and most relevant updates in the modern data stack. And with so many interesting things lined up for the coming year, make sure to stay tuned and subscribe to our newsletter to stay up-to-date.

  • Calixa: is a product-led sales platform that helps you turn signups into paid or upgrading customers. By using product data in your sales process, sales reps can convert 5x more leads and close more revenue.

    Calixa has raised a total of $16.3M in funding over 2 rounds. Their latest funding was raised on Nov 9, 2021, from a Series A round.
  • Arctype: Arctype is a fast and easy-to-use SQL client for developers and teams. It is a platform to work with teams, manage analytics, and use your queries and logic to build dashboards.

Mage: Mage is an open-source tool for building and running data pipelines that transform your data.

Here are the data tools of Mage:

Good reads and resources

  • Modern Data Stack: Which Place for Spark? : This article is about the modern data stack, which is a collection of technologies used for data processing, analysis, and visualization. The modern data stack typically includes a massively-parallel SQL engine, such as BigQuery or Snowflake, and no-code Extract/Load tools such as Fivetran or Stitch. The article is written by Furcy Pin, who notes that Spark, a popular data processing tool, is often not included in the modern data stack and that the Databricks ecosystem is often seen as an alternative to Spark. He then lists a number of pros and cons of using Spark in the modern data stack, including the complexity of mastering Spark, the difficulty of finding skilled Spark developers, and the lack of tools for organizing Spark code. He concludes by arguing that while Spark may not be the best fit for every use case, it is still a valuable tool to have in the modern data stack
  • The Build vs. Buy Guide for the Modern Data Stack: This article discusses the considerations that go into the decision of whether to build or buy components for a company's data stack. It discusses five main considerations: cost, complexity, expertise, time to value, and competitive advantage. It also provides a framework for evaluating these considerations and making a decision about whether to build or buy data tooling. The article is written by Nishith Agarwal, Head of Data & ML Platforms at Lyra Health, who has experience building data platforms for companies such as Walmart Labs, Uber, and Lyra Health. The article is part of a series on building and buying a data stack.

Upcoming data events, webinars, and summits

  • Join the virtual conference "DATANOVA" on February 8th and 9th, 2023, focused on driving business success with data. This event is tailored for professionals in leadership, analysis, and data engineering and architecture roles. Don't miss out on the opportunity to learn from industry experts and enhance your skills.

    Register for the event here.
  • Join the virtual data event "Data Engineering Live Summit" on 18th January 2023 from 10:00 am - 4:00 pm (EST) hosted by Ai+ and ODSC to get insights from leading practitioners and learn about the latest development in data engineering tools and techniques.

    Register for the event here.

MDS Jobs

  • GetGround is hiring an 'Analytics Engineer'
    Location: UK - London
    Stack: dbt, Looker
    Apply here
  • CodeSignal is hiring a 'Senior Data Analyst'
    Location: Remote US
    Stack: SQL, dbt, Snowflake, Fivetran, Hightouch, Mode Analytics
    Apply here
  • DataSF (City & County of San Francisco) is hiring an 'Analytics Engineer - Housing'
    Location: San Francisco, CA (1 day in office, must be based in CA)
    Stack: Snowflake, dbt
    Apply here

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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 :)