It's Wednesday and we are here with our brand new edition of our newsletter! I hope you guys are as excited to read it as we are to bring it to you each week 😉.
If you want to see any changes or have recommendations regarding how can we improve our newsletter, we are more than happy to hear from you! Till then share it with all the data nerds out there! 😄
Let's dive in.
This week's question: Of late, there has been an emergence of a school of thought on treating data as a product. Do you agree or disagree? Let us know why.
You can send answers by replying to the email or writing to us at [email protected]
Last week's question: As a data leader, what are the key skills that you look for while hiring a new member for your team?
Table stakes is the appropriate level of technical skills for where they are in their career. If it’s a senior position, the appropriate level of skills plus the ability to teach those skills to others.
They don’t have to have the specific skill sets we want; smart people can learn what they need to learn. What we’re really looking for is a demonstrated ability to learn combined with intellectual curiosity.
“Smart and gets things done” is always what we’re looking for. The “gets things done” part requires so-called soft skills just as much as technical skills because it’s always about making the team successful.
So the ability to communicate what they’ve done previously - not just the technical aspects but what it meant to whoever their customers were - is important. Can they see the big picture and how their work fits in? Can they work with non-technical people?
Are they a good fit on the team and in the organization? Do they bring some diversity of viewpoint that may bring something new and interesting to the team?
Are they any mixture of curious, motivated, passionate, thoughtful, personable, articulate, kind, funny, etc? Will others enjoy working with them?
Chip Young, Data Architect, Dealerware
Featured tools of the week
- Plotly makes it easy to create, deploy, and share interactive web apps, graphs, and visualizations in any programming language.
Category: Data Apps
Plotly has raised a total of $18.4M in funding over 6 rounds. Their latest funding was raised on 15th May 2020 from a Series C round.
- Phiona is a no-code data platform that makes it easy to connect data from databases, excel files, or online applications, build your transformations and automation directly within a spreadsheet interface, and share your data with your entire organization - no code or configuration required.
Category: No-code automation
Headquartered in Atlanta, Georgia, Phiona was founded in 2017.
Good reads and resources
- CDP Definition & How it's Different from a Data Warehouse: There are so many tools available to the modern go-to-market team that it can be overwhelming to figure out what you need in your stack. One of the main questions is to find out the right data tools to set Product-led growth in motion and where CDP fits in the GTM stack.
In this blog, Sandy Mangat, Head of Marketing at Pocus has explained in detail what is CDP, how it works, its benefits, and how it differs from other tools like CRMs, Data Warehouses, and Product-Led Sales Platforms. She has also discussed when an organisation needs to add CDP to its stack and when it should invest in the data warehouse.
- The Modern Data Stack Ecosystem: Spring 2022 Edition: The Modern Data Stack sphere has evolved greatly over the last few years. Adoption of and investments in MDS technologies also continues to grow. To give an overview of this ever-evolving space, Jordan Volz in this article has provided an in-depth look into the MDS ecosystem and how has it changed from Fall'21 to Spring'22, highlighting the main components shaping the MDS along with the leading tools and vendors of each of these components. The article also consists of thoughts about each of these categories based on the experience of people actually using this technology.
- Raising our data and analytics game in 12 months: In this article, Dani Solà takes us through the last 12-month journey of Clark's data team and how it grew from 2 to 7 members in just five months. He talks about the challenges he faced while using their old data platform and how they made it difficult for them to achieve analytical goals. Once these challenges were identified, they started building a new data platform following the principles of a 'modern data stack'. This led to the better handling of large volumes of data and highly improved data quality which not only helped them to make better data-driven decisions but also powered customer-facing processes.
- Data Mesh & Snowflake = Peanut butter & Jelly: Modern data stack ecosystem has seen the emergence of various trendy concepts like a data lake, data lakehouse, data mesh e.t.c. but out of these hyped and buzz words, the one which has really created an impact is Data Mesh. In this article, Nick Akincilar, has explained what data mesh is and how it helps in solving the data silos problem which data warehouse fails to resolve and eventually ends up creating more silos because of it's rigidity and lack of agility. He has also discussed why Snowflake and the concept of data mesh perfectly match each other.
- The metrics layer has growing up to do: In this article, Amit Prakash has discussed in detail about the growing excitement around the idea of a stand-alone metrics layer in the modern data stack. This has happened mainly because the metrics are defined in the BI or analytics layer where various dashboards are used to monitor them and most organizations end up with multiple BI/Analytics tools. Instead of pulling data into excel sheets and expecting everyone to calculate metrics independently, why not define the metrics in one central place for all to refer to? He has also discussed the issue with traditional BI tools and how they fail to cover an important segment of metrics that a lot of businesses care about.
Upcoming data events and webinars
- Rudderstack is hosting a webinar on 'Joybird's Warehouse-First Customer Data Stack' on 20th April.
Learn how the Joybird Team uses Snowflake, Iterable, and RudderStack to understand how hundreds of thousands of monthly visitors navigate the website, experience their customer journeys, and complete purchases.
Register here to attend.
- Data Science Salon is organising an event on 'BEYOND THE DATA STACK: CREATING A MODERN DATA EXPERIENCE' on April 19, 2022 @ 2:00 PM ET.
At this event, you'll learn how to establish a data culture that facilitates better automation, better understanding between cross-functional teams, and more effective workflows.
- Mozart Data is hosting a webinar on 'How to Choose the Right ETL Tool' on 20th April at 11 AM PST / 2 PM EST.
In this webinar data leaders at Upright Analytics and Portable will help you through the evaluation and decision process of choosing the right ETL tool.
Data startup funding and acquisition news
- Airbyte acquires grouparoo!
With Grouparoo and Airbyte joining forces, they will be offering a unique place in the open-source ecosystem where every data engineer, every analytics engineer, and every data analyst can easily move data whether for analytics or operational use cases.
- Ascend raised $31 million in a Series B round!
This round of funding was led by Tiger Global with participation from Shasta Ventures and existing investor Accel. With this round of funding the total funding of Ascend stands at $50 million.
- Transform launched MetricFlow, an open-source metrics framework for technical individuals looking to streamline & organize their process for defining and serving metrics to end-users.
- Instacart is hiring a ‘Business Intelligence Analyst’
Check out Instacart’s data stack here
- Medallia is hiring ‘Senior Business Intelligence Analyst’
Data Stack- dbt, Snowflake, Tableau, Fivetran
- USAA is hiring a ‘Data Engineer Lead’
Location- Remote, US
Data Stack- dbt, Snowflake, AWS
- Elation Health is hiring a ‘Senior Analytics Engineer’
Location- Remote, US
Data Stack- Fivetran, AWS, dbt, Redshift and Looker
- Fleetio is hiring a ‘Data Analyst’
Location- Remote, US
Data Stack- Snowflake, dbt, Metabase, Hightouch
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