BigQuery is not a Data Strategy - Part 2 - Defining Data Strategy
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In part two, we talk about defining a data strategy. What considerations does it cover?
This is the first in a 4-part series where I talk about what a Data Strategy is, how to identify a lack of or poor data
strategy in a business and it’s systems, implementing a good Data Strategy,
how to avoid those problems and what to do if you’re already experiencing them
and want to get out of data chaos, into data clarity.
See part 1
In the previous blog, we went through symptoms that demonstrate the lack of implementation, of a good Data Strategy. In this blog we’ll look at what a Data Strategy is and attempt a definition.
A strategy is the set of actions that take us towards a particular goal. Before we look at what a Data Strategy is, let’s have a look at what actions do not demonstrate a good strategy.
- Having a data dumping ground ie a warehouse or database where you put all your data, and probably directly from source
- Re-implementing the same transformations all over the organisation•Having no idea where the data is used
- No strategic planning, just dealing with issues and projects as they crop up•Putting up with painfully slow reports / queries & dashboards
- No clear data owners
- Not being able to present your data in different formats easily
- Keeping data to maybe use it one day
Data Considerations
An organisation will apply a strategy to their data in order to impact 3 main data areas: For making business decisions, identifying where to make operational improvements and first party data, created by the organisation that it can sell.
When building the Data Strategy, you should consider
- What the business wants to achieve – the Business Strategy
- That it needs to be Company-wide, and
- the quality of data & systems required, along with the skills
Building a Data Strategy
To build up the strategy, we can answer the questions:
- How does data support the Business Strategy? The Data Strategy must be derived
- What things do we want to achieve with data (Offensive actions)
- What things do we have to do with data (Defensive actions)
Two Harvard Business Review researchers created 2 classifications for Data Strategies, identifying actions into Offensive or Defensive. Here are some examples:
Offensive Actions
- Analytics for Insights
- Data Democratisation
- Multi-source Integration
- Data-Driven Automation
Defensive Actions
- Compliance
- Access Control
- Privacy
- Data Accuracy & Integrity
- Defensive
- Analytics for Protection
- Standardisation
- Governance
- Data Ownership
Data Culture
You may have heard the expression - “Culture eats Strategy for breakfast”. Whether you believe this or not, creating a culture where staff are conscious, informed and care about the company’s data, and the ways it’s used, will lead to a better adoption of the strategy and ultimately better applications of it, that support the Business Strategy.
Defining a Data Strategy
Given what we know, let’s attempt a definition:
A Data Strategy is the vision for how the organisation’s data supports the Business, with offensive and defensive actions, as well as how the data needs to be managed and which skills, are required to support the data goals of the business.
References
Leandro DalleMule and Thomas H. Davenport - What’s Your Data Strategy?
Bernard Marr - Data Strategy
In part 3, we’ll look at what the implementation of a Data Strategy looks like and in part 4, we’ll cover what to do if you already have data infrastructure and need to turn the ship around in order to solve common data problems.