Analytics for Yesterday and Today
There’s a considerable strain in today’s data analytics landscape. The sheer volume of data today requires robust analysis tools that can handle diverse structures at scale, while shrinking IT budgets and the heightened speed of business call for self-service products designed for business users.
Firms using full-stack legacy solutions are finding themselves unable to keep up with today’s changing data environment. At the same time, the next generation of analysts and data scientists are abandoning legacy technology altogether, favoring open-source options such as R or Python. Today, firms at the forefront of data innovation are augmenting their legacy systems with powerhouse analytics tools that can better handle the modern challenges of data preparation and analysis.
The Perils of Data Prep
Data preparation is easily the most time-consuming, error-prone, costly step in the data analytics process. Some companies are still using suboptimal methods such as endless Excel commands, hand-coded validation scripts, or tools like SAS, which were created for analytics, not data preparation. All of these tools are powerful, but they struggle under the weight of large data files, data from disparate systems in a variety of diverse formats, and a heightened speed of business that has zero tolerance for human error.
Many large organizations use SAS—a market leader in statistical analysis and business intelligence for the last 40 years—for both data preparation and analysis. SAS is a powerful data science and statistical tool, but many organizations are realizing that finding a modern tool made specifically for data prep would be a better use of their dollars and their team’s time than focusing on tedious data preparation scripts.
Analytics for Tomorrow: Modernize with Trifacta
A growing number of organizations are adopting self-service data preparation technologies to focus their SAS investments on what they do best—analysis. Companies save big IT dollars, democratize data analysis, and ultimately expedite analytic outcomes—a shift that is making sense for a lot of organizations.
Trifacta was created precisely for this purpose. Time and time again, we have seen our best-in-breed approach benefit customers and play a central role in modernizing their analytics tools.
Take, for example, the Royal Bank of Scotland. SAS data preparation scripts took years to hone, and made up 70 percent of the firm’s overall SAS code. But these custom scripts still couldn’t analyze online customer support chat logs due to their volume and semi-structured data. The firm added Trifacta as part of its efforts to modernize its analytics technologies, reducing time spent on data preparation by 15x.
Trifacta makes data preparation more precise, efficient, and intuitive, which is why it is routinely seen as the top data wrangling vendor by industry analysts.
Learn how data wrangling with Trifacta can optimize your SAS investments by downloading our latest whitepaper.