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Data Science

Data Science vs. Data Analytics: Key Differences

Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science and data analytics. While both fields help you extract insights from data, data analytics focuses more on analyzing historical data to guide decisions in the present. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes. These disciplines differ significantly in their methodologies, tools, and outcomes.

ELT as a Foundational Block for Advanced Data Science

This blog was written based on a collaborative webinar conducted by Hevo Data and Danu Consulting- “Data Bytes and Insights: Building a Modern Data Stack from the Ground Up”, furthering Hevo’s partnership with Danu consulting. The webinar explored how to build a robust modern data stack that will act as a foundation towards more advanced data science applications like AI and ML. If you are interested in knowing more, visit our YouTube channel now! Table of Contents.

Customer 360 for Sports and Gaming Fans: The Data Science Best Practices You Need to Know

Sports and gaming companies are forging ahead with the use of data science as a competitive differentiator. According to an industry report, the global AI in media and entertainment market size was valued at $10.87 billion in 2021 and is estimated to grow 26.9% annually until 2030.

9 AI Trends That Will Revolutionize Data Science

Data science is vital to business success. It’s our window into the likes and habits of our customers, creating opportunities to glean insights from the mountains of data we collect every day. Data has always helped businesses with decision-making, but AI is taking it a step further. So much so that today it can even be applied to the practice of creating impressive email subject lines. Machine learning for information management is now a key ally for every organization worldwide.

Interview With Director of Data Science, Michael Chang

For our latest expert interview on our blog, we’ve welcomed the Director of Data Science and Machine Learning at Included, Michael Chang. Michael helps measure and optimize workforce diversity and inclusion efforts through data. Prior to Included, Michael worked in various data capacities at Facebook, Teach for America, Interactive Corp, and eBay. Michael also enjoys teaching and is an adjunct instructor for data science at UCLA Extension and Harvard FAS.

Making Smarter Decisions with Data Science - The upGrad Way

A large amount of data is generated daily. It is very critical to understand how this ocean of information could be put to the best use. Data Science has helped organizations build differentiators using all these data points, thereby delivering a personalized experience. In the ed-tech space alone, there could be several use-cases starting from helping learners make the right choice with regards to their career decisions, guiding them through their learning journey, and finally connecting them with the most suitable career opportunities.