(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) This newsletter aims to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll share articles from various sources I found interesting. The following 5 articles/videos made the cut for today’s newsletter. 1. Data Contracts 101 by Aurimas Griciūnas The concept of a Data Contract is an agreement between Data Producers and Data Consumers on the schema, SLAs, semantics, lineage, and other details of the data being produced. Data Contracts should ..read more

Time and energy are finite resources and it’s important to use them effectively and efficiently. This requires having a good prioritization framework. In this post, I’ll share 3 frameworks that I have frequently used to prioritize. Eisenhower Matrix. Urgent vs Important matrix SourceCost Benefit Matrix. A similar 2×2 matrix that is equally relevant and helps you identify if you delete (low benefit, high cost), defer (low benefit, low priority), plan (high priority, high cost) and do (high benefit, low cost). Weighted prioritization matrix: If you want to make a decision to prioritize, you can ..read more

Few folks recently asked me on where do I allocate my team as a people manager of a double-digit (10+) analytics (data engineers, BI engineers, data science) team at Amazon. There are 5 buckets and the allocation varies week to week depending on priorities: People management activities: This bucket includes tasks where you work backwards from keeping and growing the folks on your team. E.g. weekly 1:1’s, Team meetings, Career growth sync’s, Promotion process, etc. Hiring & team building activities: This bucket includes tasks related to hiring new folks or backfilling existing roles on you ..read more

(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles/videos made the cut for today’s newsletter. (1) Data & AI landscape 2020 Really good review of the yera 2020 of data & AI landscape. Look at those logos that represent bunch of companies tackling various data and AI challenges — it’s an exciting time to b ..read more

I wanted to share 3 stories that Plato (engineering leadership mentorship platform) recently published about my managerial journey. It captures some learnings in career growth, productivity, team process and sharing the team vision. Links below. (1) How to drive a team vision as First-time manager? Paras recalls how he successfully drove a team vision as a first-time manager who too over a team without the vision and roadmap. Read here: https://www.platohq.com/resources/how-to-drive-a-team-vision-as-a-first-time-manager-1086187395 (2) How to unlock the potential of your average engineer? Paras ..read more

(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles made the cut for today’s newsletter. (1) Scaling data Fantastic article by Crystal Widjaja on scaling data. It shares a really good framework for building analytics maturity and how to think about building capabilities to navigate each stage. Must read! Here Imag ..read more

(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles made the cut for today’s newsletter. (1) Analytics is a mess Fantastic article highligting the importance of the “creative” side of analytics. It’s not always structured and that is also what makes it fun. Read here (2) Achieving metric consistency at Scale — Air ..read more

(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles made the cut for today’s newsletter. (1) The Modern Data Stack Amazing artcile by Tristan Handy explaining modern data stack. If you are familiar with tools such as Looker, Redshift, Snowflake, BigQuery, FiveTran, DBT, etc but wondered how each of them fit into a ..read more

1. Start with people: On a new team, start with meeting people. This includes your team, stakeholders and cross-functional partners. Ask them about the company, product, team, help they need and seek advice. Understand the career growth plans for every member of your team. 2. Understand product/company: Read docs. Ask questions (lots of them). Attend cross-functional meetings. Try out the product yourself. Dig deeper to understand goals and success metrics of the products and company. Recommend creating an shared live doc where you invite other folks to add their comments & suggestions. 3 ..read more

(if this newsletter was forwarded to you then you can subscribe here: https://insightextractor.com/) The goal of this newsletter is to promote continuous learning for data science and engineering professionals. To achieve this goal, I’ll be sharing articles across various sources that I found interesting. The following 5 articles made the cut for today’s newsletter. Why dropbox picked Apache superset as data exploration tool? Apache superset is gaining momentum and if you want to understand the reasons behind that, you can start by reading this article here Growth: Adjacent User Theory I ..read more