The increasing amounts of data generated by today’s modern enterprise continues to challenge organizations as they look to extract valuable insights from that data. The inability to leverage all kinds of data and the amount of expertise required from data scientists to prep data put a strain on many enterprises. IT groups need a new approach to allow for better solutions and to get data analysis tools and technologies into the hands of domain experts.
“It’s a very competitive marketplace for well trained, smart data scientists, and for the public and private sector, getting access to those resources and keeping them is very difficult,” says Andy MacIsaac, director of solutions marketing, public sector, at Alteryx. “But many times, organizations don’t always need to have that high-level resource for every data issue or need for answers. What we need to do is democratize the approach to data analytics and give access to the domain experts who can self-serve their data and analytics needs.”
Business leaders unable to access these data tools end up asking the data scientists for answers to their questions, taking them away from their larger, more mission-critical data projects. This creates friction as the two groups clash over what should be a cooperative effort.
“You want your data scientists to be working on bigger, more impactful projects,” says MacIsaac. “They don’t want to be data janitors, cleaning up data and running standard reports. They need to be tackling the big problems, because that’s what they were trained for. By lowering the barrier to analytics through new self-service and low-code data tools, you are putting a lot of capability into the hands of a larger group of people.”
Tools such as those offered by Alteryx can be quickly deployed for an enterprise, as well as public agencies, offering new insights for those groups. With automation and data cleanup tools freeing up time for data experts, they can look for new answers to new questions, and take advantage of more data sources – all without worrying about the effort to code algorithms or figure out which data is good or bad.
For example, a government agency was able to use the tools to discover whether sailors on ships during the Vietnam War were eligible for benefits related to the deployment of Agent Orange, by determining what ship they were aboard on a given day.
“Typically a business or agency will start with a business problem or challenge, and there’s always a question that needs to be figured out,” says MacIsaac. “With these tools, you don’t have to be a data scientist to get the answers if you know the data you need, pull it down and create the analysis.”
To learn more about how Alteryx can help your organization expand the use of its data analytics tools, click here.
Data Science