As tech workers, we can so easily get enmeshed in the implementation details that we neglect to see the big-picture “strategic why” that lies behind the work we’re doing.

The job of a data strategist is to focus on those big-picture possibilities and craft a plan for achieving them, and yet… as a data strategist myself, I can also fall into the trap of focusing on the how over the why.

Case in point, my STAR Framework… last week a client asked me why we need it and I realized that I’d completely neglected to communicate its significance. I was so focused on the “hows” that are involved in building a low-risk, high ROI data strategy, that I’d failed to explain the fundamentals of my approach and how that lends itself to the development and launch of successful data products.

In today’s newsletter, I’ll be sharing with you: 

1. An education on details that support this data strategy framework and

2. An opportunity for you to join a live case study and see what a data strategy success looks like in real-time.

The STAR Framework™

The STAR framework is a data strategy consulting process that I've developed out of my own experience over the last 18 years working as a data and technology consultant. 

The purpose of the STAR framework is to de-risk future data projects and products by following a methodical process that helps one select the optimal use case for substantial and reliable ROI given current state conditions within a company. 

In the context of my upcoming data strategy course, I’ll be teaching learners to utilize this approach to select 3 potential use cases and then produce an evidence-based alternatives analysis to support their selection of a single winning use case around which to build their data strategy.

The STAR framework acts as a north star to help keep a strategist oriented with respect to how the detailed stages of technical consulting work all fit together in support of their producing a data strategy plan for a low risk, high ROI data project or product. 

In a sense, it functions like a high-level roadmap for the data strategy building process.

The STAR framework is an adaptation of a process that I originally learned when working on projects with Fortune 100 tech companies, but it's completely unique from that work and I developed it purely out of my own consulting experience. 

I've led many online trainings and face-to-face workshops wherein I cover the process and teach learners how to leverage the framework; That was for organizations like insightsoftware (formerly LogiAnalytics), Saudi Aramco, Cloudera, GigaOm, Oracle, the Government of Kazakhstan, Central Bank of Malaysia, Pride Microfinance, Women In Data, and others

As you can see in the diagram provided above, the STAR Framework represents the following 4-phase approach to data strategy building.

A high-level summary of the 4-phase data strategy approach:

1. Surveying the industry

2. Taking stock & inventory of your organization

3. Assessing your organization’s current state conditions

4. Recommending a strategy for reaching future state goals

In my upcoming data strategy course, we’ll be going into A LOT more detail on how to actually apply this framework on a step-by-step basis. If you’re interested in learning the nuts and bolts of data strategy building, then please stay tuned to my newsletter and LinkedIn updates for a notification when the course is available!

For now, though, just know that Phase 1 of the STAR Framework involves surveying the industry for winning case studies and use cases … so that you can select a few of the winning cases and further evaluate whether they represent feasible wins for your company.

That’s why I’m so excited to share with you a chance to join us live on Wednesday to see and hear the story of a winning case study in action!

A Live Case Study: Winning In Action

Join us live on Wednesday to learn feasible options for quickly decreasing tech debt & achieve faster DB performance at lower costs!

Have you heard how Digital Asset Research (DAR) was able to scale seamlessly from 20 million to 140 million daily orders, at 1000x faster performance, all for 50% less cost?

Sounds pretty incredible, yes?

Join us for this live case study on Wednesday at 10 am PDT to hear from DAR’s CTO, Michael Zimberg, about how they achieved this remarkable, strategic win for the business!

Workshop Topic: How DAR Ditched MySQL for 1000X Faster Performance and 50% Lower Costs

📆 Time: Wednesday, September 20th, 10:00am PDT

You’ll learn more about how DAR drove 1000x performance improvement, and why they moved from AWS Aurora (MySQL) and Snowflake to a unified data platform such as SingleStoreDB.

This event is perfect for IT leaders, application developers, architects, data analysts, and anyone interested in building and scaling SaaS applications, especially within Fintech.

Replays are available if you save your seat now.

Yours Truly,

Lillian Pierson

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