This post highlights some of the key points to keep in mind when you are starting on data analytics journey. You may want to check a related post to assess where does your organization stand in terms of maturity of analytics practice – Analytics maturity model for assessing analytics practice.
In the post sighted above, the analytics maturity model defines three different levels of maturity which are as following:
At whichever level you are in terms of maturity of your analytics practice, it may be good idea to understand the following points to come up with data analytics projects. Believe that a lot of prior work is required to be done before starting on the analytics projects. The fact that a large volume of data is available is not enough to assure success with data analytics projects. The picture below represents the kind of homework which needs to be done prior to starting on analytics projects.
Here are the key points to keep in mind before starting on analytics projects, in particular, and analytics initiatives at large.
In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…
Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…
With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…
Anxiety is a common mental health condition that affects millions of people around the world.…
In machine learning, confounder features or variables can significantly affect the accuracy and validity of…
Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…