Companies are constantly gathering data on their clients’ behaviour. But only some businesses are able to fully take advantage of this data for their own benefit and the benefit of their customers. Without proper data science initiatives, companies bombard clients with irrelevant offers instead of carefully examining clients’ needs and serving them just the right solution.
Data science helps take the meaning out of big chunks of data that companies accumulate for years. With my guest Konrad Pabianczyk I am discovering the main insights you should understand before your company embarks on the process of building scalable models to implement data science solutions.
Who is Konrad?
Konrad Pabianczyk started out doing astrophysics research in college, went through some startups and caught his groove co-founding a deep learning startup that is still growing called Craftinity.
He then worked on the consulting and venture side and is now helping enterprises with their data science needs at Appsilon Data Science working with Fortune 500 companies all over the world.
In this episode you will learn:
- What the difference is between data science and big data? What is AI? And how these terms can be misused?
- How your company could benefit from implementing data science solution?
- How long it takes to implement a solution and how much it could cost?
- How data science will help make business decisions and save money?
- What are some particular applications of data science [case studies]?