As organizations look to advance with analytics, predictive analytics
is frequently on their road map. Businesses are interested in better
understanding their customers, predicting behavior, and improving
operational processes. They want more accurate insights and the
ability to respond faster to change. Machine learning—building
systems that can learn from data to identify patterns and predict
future outcomes with minimal human intervention—is often on
their radar.
Data scientists who engage in analysis are an important piece
of the equation. Data scientists can build new models, develop
algorithms and applications, and help the organization innovate.
However, these data scientists are not always easy to find.
TDWI research indicates that organizations are often looking to
supplement the data science team by growing the skills of business
analysts to use tools such as machine learning. For example, in a
recent TDWI survey, 51 percent of respondents said that enhancing
business analysts’ skills was one of their top two strategies for
growing their data science competencies in the organization.1
That means that organizations need productivity tools for data
scientists as well as a way to equip power users and business
analysts to perform advanced analytics. These business analysts
can work together with data scientists and other team members to
bring machine learning into the organization.