For some customers, the evaluation of a tool is less about the additional value it provides, and more about - will this save me time (and therefore, €€€)?
By quantifying these savings, it is possible to calculate the rate of return of your investment in Data Controller (ROI) and the Payback period - how long it will take before that investment is effectively recuperated.
To assist with this process, we will explain all the areas where Data Controller can save time - and finish with a calculator you can use to build your business case internally.
This represents the time spent designing and preparing the SAS code (or DI Job) that will take a business input and load it into an existing table - be that a database, a dataset, or in-memory CAS. It could be loaded with a
proc import, or an
extract transform, or even a full-blown bespoke web application for capturing the particular input requirement.
It also includes the time spent unit testing that code, documenting any macros, and parameterising it accordingly for the particular input (eg, the network share in which the input file will land). This time could be spent by multiple stakeholders. To summarise:
This represents the time taken to move jobs and programs from dev, through other SAS environments such as test, acceptance, and production. As part of this, it's often necessary to produce release documentation, perform additional deployment steps (such as setup of landing areas, permissions), prepare backout scripts, and perhaps even attend a Change Management meeting to explain the upcoming updates.
With Data Controller, once installed - this part is reduced to zero. Unless there was a need to configure a table to be editable in a test / accept environment, it wouldn't need to be done (and if it was, it would be a config change via the interface, not an actual code change).
Quite frequently, when capturing CSVs and Excel files from business users, there can be unintentional changes to the file format or data therein.
This can play havoc with the batch jobs used to build them, which typically expect a fixed structure, naming convention, directory path, and file type.
Failures in batch runs take time to troubleshoot and resolve, with knock-on impacts to downstream reporting teams.
Data Controller sidesteps the problem by ensuring that data is validated on arrival - ie, the user is unable to upload invalid data. At the same time, the process is flexible enough to ingest data with varying formats, so long as all the necessary columns are provided.
Batch incidents based on invalid files are therefore avoided.
For various reasons, data captured regularly from business users, can one day fail to meet quality standards. This typically creates a whole bunch of work:
Data Controller drastically reduces the time spent on Data Quality with the following features:
In addition, corrections can be made immediately, 'in place', with an approval step and audit trail.
In terms of data, such costs might come down to storing multiple copies of Excel EUCs on network drives, and the resultant technical debt (extra time) incurred in managing these as the copies mount up during a complex month-end process.
For audits, especially when performed by external companies, the time spent can be significant. For end-user computing systems (where source code is not secured) such audits must be reperformed every time, which can get very expensive.
Examples of fines that have been dealt in the past due to Data Quality or Data Access issues include:
The benefits of Data Controller in these areas are also threefold:
Unlike desktop based solutions (such as Enterprise Guide), Data Controller secures all code and business logic at the backend in a centralised location - which is far more secure, auditable, and maintainable then the use of local network drives.
For SAS customers using Data Integration Studio, a wealth of data lineage is available that maps source systems to target tables and vice versa.
To surface that information, it is typically necessary to make a request to an ETL developer (with DI Studio), or to step through a large number of connectors in SAS Lineage.
Data Controller provides both FORWARD and REVERSE lineage diagrams, available directly to all SAS users, that can be exported in PNG, SVG, and CSV formats.
Where end-users are using desktop tools to connect to SAS (eg Base SAS or Enterprise Guide) this can result in table locks preventing updates by other SAS users.
By using the VIEW menu in Data Controller to examine tables, no locks are held, and hence no processes are disrupted. In addition, it is possible to share links to tables, even filtered views of those tables.
Data Controller ships with dozens of features that help with Data Quality, Data Governance, and Data Management - such as:
We provide a section in the calculator for you to quantify the benefits/savings from having such features.
Download our calculator, and see how much you could save by deploying Data Controller!