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Understand

Collect

Organise

Visualise

Interpret

UCOVI

UCOVI at a glance


Strategic and imaginative use of data is crucial for a business to compete in 2022. Yet many organisations - despite more than adequate resource and time invested - are set back by data quality issues, technical debt, and labour-intensive reports that give out irrelevant, contextless or conflicting numbers.





So how should a business engage with its data? The UCOVI methodology distills it into a sequence of five steps:

  1. Understand the data you have, the data you don't have, and the data you need.
  2. Collect the data you need in the most efficient way available.
  3. Organise the data you have collected reliably, cleanly and securely.
  4. Visualise the data you have organised impactfully to show the key trends and explore further.
  5. Interpret the trends you discover in a data-savvy way.

UCOVI as the paradigm for the complete data professional

In building your own career in data or a data team under your leadership, you face two sources of confusion and complexity. First, a wide range of job descriptions used lazily and interchangeably, and second, a frankly bewildering choice of competing technologies, programming languages and frameworks that all interact with data and may or may not be what you should be learning.

The five elements of UCOVI help in both regards: they each act as discipline buckets into which technologies and specific skills can be grouped, while also simultaneously being the building blocks on which the various job roles in data - in their precise senses - are built on.

UCOVI is a clean and approachable point of reference to show exactly you where you fit into the ecosystem of data, and sign-post the learning path you should be taking to fulfill your career ambitions.


Understand
Under-stand
Collect
Organise
Visualise
Interpret
Complete Data Professional (what a business secretly expects of a Data Analyst)
CDO or Data Governance Strategist
Report Designer
Data-savvy business stakeholder
Data Engineer
Business Analyst
(How businesses see Data Analysts)
BI Developer
Data Scientist


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