Media Coverage

Five Reasons Why Your Data Science Project is Likely to Fail

Companies are moving forward with digital transformation with unprecedented speed. A recent survey by Gartner Research found that 49 percent of CIOs are reporting their enterprises have updated business models to better scale their digital endeavors.
As companies embrace these transformations, they are infusing data science and machine learning in various business functions.  A typical enterprise data science project is highly complex and requires deployment of an interdisciplinary team.  That team is often comprised of  folks such as data engineers, developers, data scientists, subject matter experts and may even be individuals with other special skills or knowledge.
Read the full article “Five Reasons Why Your Data Science Project is Likely to Fail” in eWEEK featuring Ryohei Fujimaki, dotData CEO and founder.

Subscribe

Get updates on data science, artificial intelligence, machine learning, and more.