Data transformation has been lauded since the 1970s as one of the biggest business benefits, promising everything from better organization to faster time-to-answers, lower risks, and higher rewards. But how can data transformation be so...transformative?
...but like, really, what is data transformation?
If you ask around, you might get the illuminating response of “it’s the middle part of ETL (extract, transform, load)”. Others may wax lyrical about the many methods and tools for transforming data.
But what is data transformation really, and why should we care?
Data transformation can involve processes like data integration, data migration, data replication, and data wrangling – processes that can include extraction and loading. But really what it comes down to is this: Data transformation makes data more organized, which makes it easier to use and comprehend for both computers and humans. This nicely organized, formatted, and validated data greatly improves the data quality and makes it easier for all the various platforms and systems you deal with to ingest them without losing a beat.
Think of it this way: without data transformation, integrating and moving data from one source to another is a bit like putting the square peg in the round hole. Data transformation rounds off all those rough edges so what was once a square peg now fits in neatly with its target.
Now that everything and everyone that touches data knows it has been sorted and organized accurately, we can go from raw data to insights faster and more confidently. That’s less down time struggling to standardize volumes of datasets only to have your application spit it back at you. Cloud systems stay happy without breaking down legacy, earth-bound ones. Analytics make more sense. Data doesn’t have to be “scrubbed” at the last minute because it’s already validated and squeaky clean. And our applications and systems start generating real returns.
Why care about data transformation? If you’re into getting more value, with less work, for more return out of the processes, systems, data, and people that work around you every day, data transformation might just be your thing.
Successful data transformations can yield enormous benefits. SAP even identified it as “shaping the future” all the way back in 2018. And the value of that accurate data only grows more over time.
Yet many other organizations are struggling to capture real value from their data programs, with some seeing scant returns from investments totaling hundreds of millions of dollars. Without a clear inventory of available data, data users can spend between 30-40% of their time searching for data and 20-30% of time data cleansing. It’s no wonder that the majority of CXOs consider high-quality data to be more important to an enterprise's success than management acumen.
There’s a lot more to data transformation than the SQL scripts you may be familiar with from the past. Today’s applications and technologies offer a robust range of tasks to visualize, profile, catalog, and cleanse your data in low- or even no-code environments. Selecting the right data management platform that encompasses all these things can not only simplify your transformation journey, but deliver advanced enterprise data migration, data management, governance, and analytics capabilities all within one unified, cloud-based solution.
Thankfully, you don’t have to know it all – there's a team of experts with nerd-level passion for this stuff that’s already done all the research for you. Comprehensive solutions like the Syniti Knowledge Platform have a proven reputation for reducing transformation risks with a targeted, data-driven approach for upgrading systems.
Ready to chat with someone about the next step in your data transformation journey? Reach out to us here.