Category Archives: data engineering

Data Quality Challenges for Analytics Projects

data quality challenges for analytics projects

In this post, you will learn about some of the key data quality challenges which you may need to tackle with, if you are working on data analytics projects or planning to get started on data analytics initiatives. If you represent key stakeholders in analytics team, you may find this post to be useful in understanding the data quality challenges.  Here are the key challenges in relation to data quality which when taken care would result in great outcomes from analytics projects related to descriptive, predictive and prescriptive analytics: Data accuracy / validation Data consistency Data availability Data discovery Data usability Data SLA Cos-effective data Data Accuracy One of the most important …

Continue reading

Posted in Analytics, data engineering, Data Science. Tagged with , , .

Data Science vs Data Engineering Team – Have Both?

Data engineering vs Data Science

In this post, you will learn about different aspects of data science and data engineering team and also understand the key differences between them. As data science / engineering stakeholders, it is very important to understand whether we need to have one or both the teams to achieve high quality dataset & data pipelines as well as high-performant machine learning models. Background When an organization starts on the journey of building data analytics products, primarily based on predictive analytics, it goes on to set up a centralized (mostly) data science team consisting of data scientists. The data science team works with the product team or multiple product teams to gather the …

Continue reading

Posted in data engineering, Data Science. Tagged with , .