For most organizations, buying is the better choice, unless you have a team willing to maintain the catalog for years. Building a first version is quick: a list of tables, a few definitions, a search field. The real cost comes later. Connectors break when your source systems are updated, metadata becomes outdated, and someone has to keep following up with owners. Building only pays off if you need something no product offers and can dedicate people to that work for the long term.
Why building your own looks cheaper than it is
Most teams compare building and buying based on the first few months. That is the wrong timeframe. Building is the easy part. The cost lies in everything that follows.
Here is an example. The BI team builds a glossary in SharePoint, with a script that reads the Power BI workspaces every night. A few sprints later, it is ready. Everyone is happy. Six months on, a new source has been added, an API changes, and the colleague who wrote the script leaves. Nobody dares touch it anymore. The definitions are no longer accurate, and business users stop checking them.
That does not make it a bad team. It is the normal lifecycle of internally built software that nobody manages as a product.
What a data catalog really needs to do
A list of tables is not a data catalog. If you build your own, you are also building:
- Connectors to your sources: Power BI, your data warehouse, your ERP. Each source has its own APIs that change regularly.
- Automated scanning and lineage, so you can see which table feeds which report without someone tracking it manually.
- Definitions and owners, with a way to approve and review them.
- Permissions and access, so people only see what they are allowed to see.
- Search and an interface that business users can understand without training.
- Visibility into data quality, so readers know whether today's figure can be trusted.
Each of these components is a project in its own right. Together, they form a product you need to keep maintaining.
Where do the costs lie after launch?
The cost of a catalog is not in the first version. It is in the work that comes back every month.
- Technology. Sources change, APIs evolve, security updates need to be applied. If you build it, you are responsible for upgrades too.
- Content. Definitions become outdated, owners change jobs, new reports are added. Without ongoing attention, a catalog becomes an archive within a year.
- Adoption. Users ask for new features, and an internal tool competes with every other team priority.
- Knowledge. Often, only one or two people know exactly how it works. When they leave, the catalog goes with them.
Buying a catalog takes most of the technical work off your hands. The content is always your responsibility. So another question is: which product makes that content work easiest?
Building, open source or buying: how do you compare?
| Approach | Quick first version | Who maintains the technology | Who keeps the content up to date | A good fit when |
|---|---|---|---|---|
| Build your own (wiki, SharePoint, custom app) | Yes | Your own team, always | Your own team | The scope is small and stays that way |
| Self-host an open source catalog | Fairly quick | Your own team: hosting, upgrades, connectors | Your own team | You have a strong data engineering team willing to manage it |
| Enterprise governance suite | No, often a lengthy process | The vendor | Data stewards and a governance team | You have or are building an extensive governance organization |
| Lightweight catalog visible within your reports | Yes | The vendor | The assigned owners, as part of their own work | The business primarily wants to understand and trust reports |
When building your own does make sense
Building is not always the wrong choice. It can be the right one if:
- you have one or two sources and that will not change;
- your data engineering team is willing to manage a catalog as a product, with time and budget for maintenance;
- you have a very specific requirement that no product meets, and that requirement matters more than everything else.
If you are unsure, start by asking who will manage the catalog in two years. If you cannot name someone, building is a risk.
Five questions before you decide: Purpose, Readers, Sources, Maintenance, Ownership
- Purpose: what problem does the catalog solve, and how will you know it has been solved?
- Readers: are they data engineers, analysts or business users reading reports?
- Sources: how many systems do you need to connect, and how often do they change?
- Maintenance: who looks after connectors, upgrades and security, now and in two years?
- Ownership: who keeps the definitions up to date, and does that fit into their regular work?
Where dScribe fits
dScribe is a data catalog you buy rather than build, designed for organizations whose main goal is to help business users understand their reports. In Power BI, the browser plugin displays definitions and owners on the reports your team already opens, and shows failed runs as alerts. You can see data quality issues together in one place, in a marketplace within the dScribe app. dScribe only reads metadata; your actual data stays where it is. It crawls metadata from your systems, including older ones, and builds an inventory, so your team does not have to maintain its own connectors. Smart suggestions help with the content work: they help define terms and KPIs, link them to the reports and datasets where they appear to be used, find duplicates and help build lineage. Defining KPIs still involves some manual work, but the suggestions make it easier.
The bottom line
The question is not whether you can build a data catalog. Almost any BI team can. The question is whether you want to maintain it, every month, even after the person who built it leaves. So compare the second year, not the first version. Who is still maintaining the technology and definitions at that point determines whether your catalog stays alive or becomes an archive.
Frequently asked questions
How much does it cost to build your own data catalog?
The build is rarely the biggest part. Factor in the people who will look after connectors, upgrades, security and user requests over the coming years. That work continues for as long as the catalog exists.
Is an open source data catalog free?
The software is; using it is not. You have to host it, upgrade it, connect it to your sources and support it yourself. That requires a team with ongoing responsibility for the work.
Can't we just use Excel or SharePoint as a data catalog?
For an initial list of definitions, yes. The problem is that a list like this is separate from your reports and sources, so it becomes outdated and few people read it. As soon as you need automated scans, lineage or visibility into data quality, you hit its limits.
When is buying a data catalog better than building one?
When you have multiple sources, when business users need to use the catalog, and when you do not have a team willing to maintain it as a product. That is the case in most medium-sized and large organizations.
How do you get started with a data catalog without a major project?
Choose one domain and a handful of widely read reports. Agree on definitions and owners for them, and make those visible where people read the reports. Only expand once that domain is actively used.