The emergence of the term ‘data science’ has left many puzzled as to what exactly it encompasses. Bojan Cukic, chairman of the Department of Computer Science at UNC Charlotte collaborated with the Charlotte Business Journal to conduct a Q&A session with technologists, or in other words ‘data experts’, to spell out the meaning of ‘data science’. The group comprised of Rishi Bhatnagar (CEO – Syntelli Solutions Inc.), Bill Doyle (Chief Revenue Officer – RapidMiner), Marc Vaglio-Laurin (Sr. Product Manager, Advanced Analytics – Qlik) and Rick Doody (CIO – SPX Corporation). The experts shared their experiences and insights in working with data scientists who were responsible for transforming businesses using data.
Here’s a summary of the points discussed during their conversation:
What Is ‘Data Science’?
- Data science is about bringing information from multiple related or unrelated data sources together for decision making.
How Did ‘Big Data’ Emerge?
- The availability of improved computing power and cheaper storage, led to an increase in the amount of data being captured. Everyone worked towards a building a big data strategy, collecting a lot of information but failed to do anything with it.
What Is The Next Step In Gaining Competitive Advantage?
- Businesses have maximized their return on investments with improvements in manufacturing, marketing, and advertising. Now, data and technology together, have opened up new opportunities for efficient use of data.
- Businesses like Wal-Mart use data to their advantage by using analytics for price, supply chain, packaging, and customer satisfaction.
Importance of Data Interpretation
- Everyone can be a guru at spreadsheets, but the real task is to make inferences from the data and thereby make decisions to drive the business. The key is to Collect, Analyze and Manipulate data and data visualization helps with this.
- If data scientists didn’t have a proper way to interpret data, their interpretations would go sideways.
Taking Data Visualization One Step Further
- Using visualization in a predictive mode, can be a game changer.
- The holy grail is when the process is automated and works seamlessly to guide decision-making that results in more revenue.
- An effective planner in a manufacturing organization must know which knobs to turn to optimize a process without sub-optimizing another.
More information on the positive side effects of data analytics, technologies that enable big data, and ways to ensure growth of talent in this riveting discussion among these experienced and insightful ‘data experts’ here: https://bit.ly/2m1M50E