The thing that determines your success is not whether you can access this resource but how efficiently you can process and refine this raw resource into a form that can be used for a purpose beneficial to you. Companies are not sparing any expense when it comes to processing data that can be used to better understand and target their customers or to monitor the efficiency of their internal processes.
And as with any processing and refinement, it all boils down to two factors that determine efficiency: the tools at your disposal and the methodology you use.
Companies use reports every day to present a distilled, easily understandable, and highly adaptable representation of the data on which the company’s everyday decisions stand. From information like business profitability and performance by region, to the monthly ability of individual departments to reach their KPIs.
Each report contains dozens of metrics by which the company’s objectives are measured. Many companies would be content with leaving the metrics at the mercy of whoever creates that given report, but smart companies which strive to be in control of their data – like Accurity’s customers – immediately recognize two major opportunities to consolidate and enrich their reporting with added value: making sure the data in each report is correct and that each metric is correctly understood by everyone.
Why are these such opportunities? They might seem like obvious things to do. But that very obviousness is the reason these are so often overlooked. It is easy to overlook that you have no idea where the data in a report comes from, or that you would not be able to tell if the data changed. It is easy to overlook that Bill from Marketing has a different interpretation of “Customer Activity” than Abby from Sales. And that is a problem, because they look at the same report, but see something different. And when understanding of data diverges among your decision makers, how can your decisions be efficient?
The very first thing to be done is making sure all metrics are universally understood. There is nothing extra that you would need in order to do that – only the report metrics themselves – and it is the cornerstone on which further data governance initiatives can be built.
Defining what individual metrics mean requires all stakeholders, who get value from them in reports they are contained in, to work together on definitions that make sense to all of them.
Just this simple act of finding common understanding across departments goes to great lengths to improve reporting efficiency. It is also a contributing factor to removing redundancy in reports of various teams and departments that would otherwise have used their own reports with their own metrics, increasing reporting overhead.
In data governance, a collection of defined metrics is called a business glossary. But a business glossary does not have to be just a passive list of terms and their definitions – at least, it is not in Accurity.
The main purpose of a business glossary should be to enhance both the original data, and the end-point implementations of it, with context. Defining the metrics are the most basic way to do it. Another function a business glossary fulfils is the assignment of synonyms and abbreviations.
Many longer metrics are abbreviated in order to fit the reporting widget they represent. Not having a tangible and searchable connection between a main metric and its abbreviation can lead to duplicity within a business glossary.
Of course, the most useful connection to have would be between the metrics definitions and their implementations in reports themselves. That way, looking up a correct way to understand a report would not be a matter of several minutes of searching, but only a few seconds.
Business glossaries, such as the one in Accurity, include a downloadable browser extension/add-on that connects the application to any report, document, or other text opened in the browser, by scanning the text and offering definitions directly as the report is being used.
This functionality not only scans for the metrics themselves, but also takes the attached synonyms into account and highlights them too.
Once all metrics are properly defined, and an easy connection between these definitions and their implementations in reporting is established, then comes the time for the next step. One which significantly contributes to the creation of centralized and consolidated enterprise reporting overall.
Reporting metrics do not exist in a vacuum. They represent not only real data, but also real things within your organization. Many are connected to one another. Many are dependent on one another. Many require data under another metric in order to be correctly calculated.
Normally, each time a reasonably sized company would need a part of these relationships mapped in order to update their reporting, it would cost several months’ worth of work of a team of business analysts.
Luckily, a reasonable metadata management platform can solve this predicament for its customers, easily saving all that time, work, and money, by establishing connections between metadata objects that represent these metrics and all other objects relevant to them.
The trick is to map out these relationships in detail only once, document it well and then reuse when required with minimal extra effort and maximal extra understanding of those connections. Remember that it is not just writing those connections down on a sheet of paper – every object is connected to every other relevant object and to real data behind those objects, in a complex web of understanding that – once you build it – will become irreplaceable.
In Accurity, these connections between metrics are located in the business glossary, and they allow users to establish links, calculation rules, and hierarchies between individual metrics.
Metadata management platforms are not just used to document and describe metrics and other business metadata. They document technical metadata as well. Information about what databases, tables, and columns you possess and what technical parameters and contents does each of them have.
This kind of metadata is stored in a data catalog. Having a documented catalog of your entire data infrastructure is a reward in and of itself. However, there are ways to make it beneficial for the reporting use case as well.
Reports often have to be updated, redesigned or scrapped and created anew as requirements from the management, the mother company, or the regulator change over time. So, each time this happens, it is important for the reporting team to know where the data that they need to create the graphs for that particular report are located.
Again, without proper documentation, every time such a project would arise, this would take a lot of manual effort and asking around between the reporting team and the data team.
However, now that we have every metric defined, stored, and connected, both their implementations in reports and to other metrics as well, this redundant work can easily be removed by adding one more connection.
Solid metadata platforms allow for metrics to be connected to metadata representations of real data locations through what is called business data lineage – a relevancy connection between a business glossary object and a data catalog object. You can discover more about visualizing business data lineage in our Accurity Enables Non-technical Users to Work with Interactive Data Lineage Diagrams blog post.
How is business data lineage useful to reporting? That is simple. Instead of having to ask three or more busy people to get the name of the database and a further three to get the name of the column and access information, you can, using the pre-established network of connections, browse from the metric in the report itself down to the exact name and characteristics of all the locations that metric has its data stored.
Fun fact: Using the Accurity platform, any user can move from a metric on a PowerBI report sheet to the exact name and location of that metric’s database column in precisely 3 clicks and under 10 seconds! Without any assistance from someone else to boot!
This has not just been a general post about what a metadata platform, such as Accurity, can do for your business. This is an actual use case and the exact way one of our large e-commerce customers benefits from using Accurity to achieve trust in data, mutual understanding and cooperation, and consolidated reporting, all of which they base their decision making on. This methodology works.
As I mention in the beginning of this article, this is a benefit readily available to everyone who stores and uses data. The only thing you need to do is grasp it, polish it, and make it shine.
If your organization would like to take these steps towards ensuring its data and reporting are reliable and trustworthy, why don’t you schedule a demo with us? Our team will gladly show you, hands on in Accurity, this use case or many others!