by Shelley Osborne, Author of The Upskilling Imperative
Automation skills let data scientists focus on strategy
With the growth of data analysis skills, data scientists can now spend more time exploring complex business questions. How? Machine learning techniques that provide insights and predictions far beyond the typical dashboard. But preparing the massive amounts of data needed for those pipelines is no simple task. Automation tools help data scientists speed up the process.
“Recently, huge strides in machine learning and artificial intelligence have allowed for the creation of new data science tools that automate a variety of repetitive tasks,” says Jose Portilla. “Data scientists have more time to focus on developing clear business solutions instead of cleaning data.”
Machine learning automation skills
Programming libraries and machine learning techniques power the deep business insights data scientists extract from vast amounts of internal and customer data.
Data automation tools
To free data science teams from the minutiae of manual data preparation, leaders are investing in training teams in data automation tools.
What does this mean for your organization?
Data maintenance and governance are key pieces of a company's data architecture. They're also areas that companies are continuing to untangle from legacy software and data issues. Humans, not algorithms, are the ones who understand where data is coming from and how it should be used for machine learning purposes. But, to use their time efficiently, companies must equip employees with training in the automation practices their competition is rapidly adopting.