Yagnesh RamalingamTopic
Governed data
Start here if nobody trusts what comes out of the warehouse.
Enterprises did not underinvest in data access. They over-invested in access and underinvested in ownership. A lake with no owner is how two dashboards start telling two stories.
The explainer
Governed data. In practice.
Most enterprises did not underinvest in access. They bought the warehouse, the pipelines and the self-service tool, and then discovered that nobody would stake a decision on what came out. Access without an owner is inventory. Inventory is how two honest teams produce two honest numbers.
The four things access does not include
- An owner. A named person who can refuse a change, not a council that meets monthly.
- A quality bar. What ‘good enough to decide on’ means for this source, written down.
- Lineage. Which system the number came from, and what happened to it on the way.
- A purpose. The decisions this source is allowed to feed, and the ones it is not.
Miss any one of them and every answer stays contestable. That is why another year of BI spend does not shorten the meeting. The semantic layer is the contract on top of this foundation. Without the foundation, the contract freezes whatever folklore was already in the extract.
What it is not
It is not a catalogue. A catalogue lists assets. Governance says who may change the meaning of one of them, and what the number is for. It is also not a reason to stop exploration. A sandbox can be messy. A number that enters a forecast, a board pack or a compensation plan cannot.
When two dashboards disagree, start here only if you cannot name the source’s owner. If you can name the owner and the charts still diverge, the missing piece is the metric contract, not another stewardship meeting. That disagreement has its own article.
Where to start
Pick the source behind the metric the room is fighting about. Write the owner, the quality bar, the lineage and the purpose on one page. Then write the metric contract on a second page. Do not start with a governance operating model for the whole estate. The estate will not sit still for it, and the meeting is next Monday.
Articles
Articles on governed data
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Keep going
Related topics. Where to go next.
- Narrower topicSemantic layerStart here if two dashboards show different numbers for the same thing.Explore the topic
- TopicDecision latencyStart here if a simple question takes weeks to become a number anyone will act on.Explore the topic
- TopicExtended Planning & Analysis (XP&A)Start here if every planning cycle begins by reconciling last month.Explore the topic
- TopicAgentic analyticsStart here if you are being asked to put an AI assistant on your data.Explore the topic
Case studies
Case studies. What changed, and how.
- Before ZerentroMulti-brand consumer enterprise
11 days→4 hours
Decision latency on the weekly pipeline question
Three answers, one Monday question
A weekly pipeline question that used to take 11 days now returns a sourced answer the same afternoon.
Read the case study - Before ZerentroEnterprise operations
18→6 days
Monthly forecast cycle
When the forecast became a political artefact
Forecast cycle time dropped from 18 days to 6, because the argument about last month’s actuals stopped happening twice.
Read the case study
Questions about governed data
What is governed data?
Governed data is source data that has an owner, a quality bar, lineage, and an agreed purpose. Access without those four is inventory, not a foundation.
What does Yagnesh Ramalingam say about governed data?
Enterprises did not underinvest in data access. They over-invested in access and underinvested in ownership. A lake with no owner is how two dashboards start telling two stories.
Why is BI adoption still so low after years of investment?
Because organisations bought access and assumed a trusted answer would follow. Access is whether you can reach the data. A trusted answer is one that survives being questioned, fast enough to still matter. If a tool has been available for years and people still route around it, the tool was not the thing they needed.
Is a data catalogue the same as governed data?
No. A catalogue tells you an asset exists. Governed data tells you who owns it, what standard it has to meet, where it came from, and which decisions it is allowed to feed.
Who should own a source?
The function that will defend the number in the meeting, with the data lead accountable for the pipeline that feeds it. An owner who cannot refuse a change is a name on a slide.
Do we need a tool to start?
Not for the first five sources. A shared page and a named person come first. Software is how you stop that page from rotting, not how you create it.
Work with me
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