A survey conducted by Gartner reveals a startling statistic: the average tenure of a CDO is a mere 2.4 years. This eye-opening finding highlights the challenges faced by Data leaders and underscores the importance of equipping them with the essential technical skills necessary for long-lasting success.
Although, as data leaders, there is a significant focus on soft skills as it should be, unfortunately, in the early days, the lack of technical skills sometimes creates a shortfall of knowledge leading to shorter tenures.
Today, let’s explore three critical technical knowledge areas that empower data leaders to navigate the complexities of data analytics, drive innovation, and ultimately make a lasting impact on their organisations.
1. Ability to Interpret and Communicate Architectures
Architecture knowledge is critical to your success as a data leader.
One of the first tasks you will have to deal with is ensuring the platform from which the organisation is being served its data is robust and reliable. However, leaders with a lack of architectural knowledge struggle to understand and articulate its importance of it.
Data Architecture is a technical skill that should be married with communication as the soft skill to land the message to technical and non-technical stakeholders. This also involves analysing and interpreting various data architecture components, such as databases, warehouses, lakes, and pipelines.
Effective communication of architectures facilitates collaboration and decision-making.
The example questions you should be able to ask / answer:
- What are our customer-facing systems?
- How often do we extract information from them?
- Where in the organisation is all the data stored?
- What does a usual data flow look like?
- How quickly can we analyse the data once captured?
- Which data feeds our AI / ML models?
- How do we currently govern this data / how should we govern this data?
- How good is the quality of the data?
- What are our agreed data definitions?
2. Defining Data Value from Use Cases
If the data is not providing value, it’s a liability, not an asset.
As a data leader, you should be able to look straight through the fluff and noise and pinpoint the data that ultimately solves the business problem. Data leaders must also possess the ability to assess the strategic objectives and requirements of the organisation and translate them into actionable data-driven use cases.
This skill requires a deep understanding of the business domain and the available data assets.
The example questions you should be able to ask / answer:
- What are our critical data assets?
- How do data assets translate to products?
- How under-investment in Data Quality impact end business use cases?
- Which business use cases are we resolving using this data?
- How is revenue generated, and risks mitigated using this data?
- What are the CFO / CRO / CxO priorities, and how does my data function enable this?
3. Understanding Complexity and Redundancies in Your Data Estate
Simplify data estate, and amplify your efficiency.
Along with revenue generation opportunities, there should be a focus on cost efficiencies. Successful organisations quickly outgrow their IT and Data estate. Data leaders must understand their data estate and areas that can be improved or simplified. Uncovering redundancies lets you streamline operations, optimise storage, and enhance data quality.
This skill leads to a simplified, efficient & modern data estate that drives valuable insights and business outcomes.
The example questions you should be able to ask / answer:
- How many data sources or storage areas are redundant?
- Where are data silos in an organisation, and what are the impacts of those?
- What are cost efficiencies if certain operational data stores are decommissioned?
- How can complexity be reduced to simplify data governance and quality?
- Which business processes depend on the complex part of the data estate?
Conclusion
Soft skills continue to be essential; you must be able to negotiate with your peers, communicate with various audiences, simplify complex topics etc. However, you must also possess technical skills to earn the confidence of your teams and the Leadership.
Implementing Data Quality (DQ) is one of the hardest parts of the job. If you want to sell DQ to your leadership teams and implement core aspects of it, then check out my FREE Ultimate Data Quality Handbook. By claiming your copy, you’ll also become part of our educational community, receiving valuable insights and updates via our email list.
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