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### Live Session 1 - Data team structures

#### Objectives
1. Understand the considerations into organising your data team and its impact on your overall organisation.
2. Understand that there is no one best solution, and organisations need to adapt their data team structures to their needs and constraints.


#### Reading resources

**Mandatory readings**
* https://www.metabase.com/community_posts/how-to-structure-your-data-team-to-support-organizational-goals

    * Good discussion on pros and cons of centralised and decentralised teams

* https://snowplow.io/blog/data-team-structures-guide/ - Focus on guiding principles
* https://www.getdbt.com/data-teams/centralized-vs-decentralized/

    * The example from a company is quite interesting
* https://medium.com/super/how-should-our-company-structure-our-data-team-e71f6846024d
* https://opendatawatch.com/publications/the-data-value-chain-moving-from-production-to-impact/
* http://dataeconomy.eu/data-value-chain/#page-content

* Please read the highlight paragraphs of our recommending book: Thinking In Bets, summarized by Cliff: https://docs.google.com/document/d/11h_X-gBUQiUTVJukKYuxuTbikB3mMNeJiMFyu5NL5Mw/edit?usp=sharing 

**Optional Readings**

* Book - Thinking In Bets：https://www.amazon.com/Thinking-Bets-Making-Smarter-Decisions/dp/0735216355

#### Other preparation
Please allocate some time to observe and understand the data organization within your current company, as well as the stakeholders and requirements for collaboration with the data department. We will complete your current stage of data organizational map in class.




**Key takeaways**
* Your company's data needs will determine how you should best configure your analytics set up
* As your company's (data) needs change, your analytics set up will have to evolve
* What we can cover are first principles in the data value chain. How it can apply to your organisation needs to depend on your understanding of the methods and your organisation

**Extra questions**

* What tasks needs to be done in order for your organisation to get value out of data?
* Does your organisation have the right people to do them?



### Course Focus
This course is suited for professionals with at least two years of working experience in a data role as an individual contributor, where he or she frequently processes and analyses large volumes of data. 

Participants must already be comfortable with basic analytics terminology and frameworks, and be willing to discuss technical data topics with his or her peers. 

While we will not cover any programming in this course, we will discuss many principles behind our modern data tech stack. At the end of the course, participants can expect to gain a greater appreciation on the impact of data on their organisation beyond their own individual contributor role, and understand what it takes as a team to push their own organisation to be data driven.


### Learning Format
The course is broken down into these components: (1) Self-reading (2) Live sessions (3) Online discussions & group assignment.

* We expect participants to finish about two hours of reading materials per week before the class. Interested participants can dive deeper into the additional readings provided for each week.

* We will provide exercises to get participants to pen down their thoughts and learnings throughout the course.

* During the live sessions, the instructors will share the key ideas and best practices relating to each topic, while also highlighting edge cases and counterfactual examples from the field that may go against these best practices.

* Participants are encouraged to ask questions and share their thoughts in both the live discussions and Discord channel.



### Case Introduction: GreatTech Acquires TechWonder


In a significant strategic maneuver set to redefine its competitive position, GreatTech, a well-established US-based tech powerhouse, is acquiring the German firm TechWonder. This acquisition is a calculated attempt to augment GreatTech’s European market share, marking a crucial milestone in its relentless quest for global expansion.

Historically, GreatTech has considered itself a vanguard in the tech industry, ceaselessly leveraging technological innovations to drive industry transformation. However, the passage of time and rapid evolution of technology have ensnared GreatTech in a web of technical debt.

The core of GreatTech’s system, steeped in C++, has always been a matter of pride for the company’s engineering team, notably for its efficiency. Despite the language being outmoded, it allows the system to support a vast number of customers with limited server requirements, showcasing an impressive degree of optimization.

Contrastingly, TechWonder, a youthful German firm, runs on a Java-based system, demonstrating the company’s affinity for modern tech trends. Its engineers have become adept at working with cloud-based solutions, their default choice for new developments. Yet, this reliance on cloud technologies has led to significantly higher technical operation expenses, impacting the company’s bottom line.

The proposed acquisition’s synergies and differences present an intricate puzzle. The ensuing challenge lies not only in seamlessly integrating these contrasting systems but also in managing the varied expectations and working styles of the two engineering teams.

In terms of customer base, GreatTech maintains a commanding lead with thrice as many customers as TechWonder. The acquisition brings with it the potential of converting regional customers — currently restricted to the US or Europe — to global contracts, reinforcing the importance of seamless system integration to meet customer expectations.

As the one overseeing this integration, you are at the helm of a pivotal decision: choosing which system to retain and strategizing on how to minimize the disruption. This choice is not merely about technical preference but also a matter of aligning with business goals, managing operational costs, and preserving customer satisfaction.

In summary, the merger of GreatTech and TechWonder heralds a new era of consolidation, technological refinement, and market expansion. It presents a complex yet promising challenge: navigating the technical intricacies of the merger, aligning the systems in a way that maintains customer trust, enhances service offerings, and ensures the continued dominance of GreatTech in the global market. The onus is on you to guide this critical process, making decisions that will shape the future of the new entity.
