Large enterprises invest heavily in modern data and analytic environments. That can be seen in growing revenues for big data and analytics — estimated to be $260 billion in the US by 2020, according to IDC. But while the cost and effort it takes to implement and maintain data environments can be pretty easily measured in dollars (and euros and yen), sweat, and time, measuring the “value” of those environments is much more difficult.
One of the clearest indicators of the impact of the investment comes through the lens of the data-driven organization. A data-driven organization is deriving business value from data and analytics. The definition is simple enough, but how do you measure the connection between the environment and the end result?
Conventional data warehouses and business intelligence tools provide a means for technically-oriented DBAs and admins to measure the usage of their investments. If a report is run often, the business must be achieving its goals and driving data-driven decisions, right? Well, not exactly.
Usage does not tell you much about the actual value gained from analytical investments. Usage rarely directly translates into how much real insight and business value gets created. Important questions invariably remain. Are the analysts using the right data for their decisions? Does the usage reflect net new insights or are knowledge workers recreating work? This is where a modern data catalog can provide much-needed insights.
The Data Catalog: A Window into the Data Environment
More than 150 enterprises turn to Alation to boost analytic productivity, foster collaboration, and create a data culture by making it easy to find, understand, trust, use and reuse data. And whether your environment consists of a data lake, cloud data warehouse, business intelligence tools, or (likely) a combination of tools and repositories, Alation also offers insight into the activity, use, and outcomes of your analytic investments. Alation lets you see what data assets are being used, how those data assets are being used, and enables self-service for a broader spectrum of data consumers. Armed with this information, enterprises can draw a direct line between their analytics investments and business value.
Let’s take as an example, one large financial technology institution customer that worked with me to quantify their investments with Alation. We were able to find a two-fold set of conclusions. By using the Compose SQL editor within Alation to surface relevant data recommendations, the organization saved a total of 17 days (136 hours) across their analyst teams. Additionally, the customer realized that many of their analysts were not standardized on a single query tool and, instead, relied on a variety of query tools and code repositories. We were able to use the data catalog to quantify concrete returns on investment as well as further improve their analytical environment.
By unlocking the clues to the existing value in customer’s analytics investments, the Alation Data Catalog can extend data-driven use cases — effectively creating more value where value already exists. For example, analysts can spend their time focusing on driving real insights, as opposed to reworking and trying to understand mysterious data. By understanding the key data assets that analysts are focused on, data stewards and analytic stewards will be able to respond to changes in their data environment with greater agility, focusing their efforts where they can make the most impact. Data management IT teams can use the insights gained from the data catalog to plan more effectively and drive important initiatives like cloud migrations by prioritizing the data that is used most rather than migrating data with little organizational value.
An On-Ramp to Productive Self-Service Analytics
Of course, measurement is one thing but in order to match the sophistication of analytical investments, enterprises also need more sophisticated tools to better leverage and govern those environments. With Alation, data consumers have an easy way to search for (using natural language search) or query (using the Alation query tool, Compose) without having to make requests of IT. Data consumers can also use the Alation Data Catalog to share the analysis they have created, remove redundancy, and better understand how to use data assets for accurate analysis.
If an analyst is starting a new project, they often have to do their best to find and understand relevant data assets. That could mean wandering the halls (sometimes literally) asking around and hoping to find out if someone has done a similar analysis — a huge challenge, especially in a large enterprise. And, when they find something that might be relevant, they often have to try and guess the intent of its creator. With Alation, knowledge workers can search for or write a query in Alation and find similar projects with the context needed to understand whether the data asset is relevant and find the experts on that data asset in case they need further clarification — with huge benefits to their productivity. In a recent Total Economic Impact Study of the Alation Data Catalog conducted by Forrester, researchers estimate that analysts shorten the time to complete a project by 70% with Alation with half of that time applied directly back to analysis tasks. The same Forrester study found that using Alation’s TrustCheck feature allows knowledge workers to understand when they are using inappropriate or incomplete data logic in their queries.
As analysts build insights and reports, data stewards and analytic stewards require tools to ensure analysts are maximizing their data investments. Stewards need to make sure data consumers are using the right data for analytics and curate the datasets that are most needed. With Alation’s change log, stewards are aware of all curation and metadata changes happening across their data environments. If an data consumer incorrectly uses or curates a data element, Alation will alert the stewards about the change, and stewards can quickly act and correct any issues. Alation will also show the popularity of tables and columns to guide stewards in their curation efforts, ensuring that they are focusing on the data assets that have the most impact within the organization.
The Foundation for Managing Change
The natural lifecycle of data investments requires changes to the underlying architecture. These changes are often difficult to plan, as legacy data environments are rarely tracked outside of pure IT use cases. With the Alation Data Catalog, non-IT users can understand the key data sources to plan and scope their architectural moves. Customers that want to move to a cloud DB can spend and negotiate for the right-sized data environment, rather than guessing what appropriate usage patterns should look like. And while the architectural change may be significant, Alation provides a single interface for both legacy and future state investments, making the change seamless for data consumers. Because Alation sees how data is being used across systems, the business can be confident they can deprecate legacy sources once users have stopped using old platforms, and IT can be sure that their new investment is being adopted.
While measuring the value of your analytics environment more accurately is critical to ensuring that your data investments are creating value, the ultimate benefit of data catalog is what the business is able to achieve. While putting a value to things like increased collaboration, uncovering insights, and creating a data culture can be tricky, Alation customers have achieved incredible outcomes by making the Alation Data Catalog a part of their analytics environments. From Pfizer finding insights into rare diseases with Alation as part of the companies Virtual Analytics Workbench and American Family Insurance increasing data literacy across its organization to Munich Re finding new ways to protect against the risk of natural disasters, innovative enterprises are finding creative new ways to create more value from their analytics investments.