Data analysis comes with the goal of deriving useful information from data, suggesting conclusions, and supporting critical business decision making. There’re lots of data analysis tools that can be utilized to help a business to get a competitive edge. If you’re trying to step into the field of data analysis, it’s extremely important to have a good working knowledge of the most commonly used data analysis tools. In this post, we’re going to discuss five such tools by learning which you’d be able to propel your career in data analysis.
In the last few years, big data has become central to the tech landscape. You can consider big data as a collection of massive and complex datasets that are difficult to store and process utilizing traditional database management tools and traditional data processing applications. The key challenges include capturing, storing, managing, analyzing, and visualization of that data.
In recent years, machine learning has been one of the most talked about tech topics and is being applied to businesses widely. Put simply, this application of artificial intelligence allows computers to learn and improve without being programmed directly. The revolutionary technology presently forms a highly crucial aspect of countless established, as well as, burgeoning industries. Let’s have a look at the key reasons why you should start preparing now to become a machine learning professional.
A significant number of newcomers in data science tend to spend a huge amount of time to develop theoretical knowledge and earn certifications only. While theoretical knowledge is certainly required to become a good data science professional, recruiters don’t put much emphasis on certifications only. Instead, they tend to evaluate the potential of a candidate by going through his/her work.
If you’re interested in learning artificial intelligence or machine learning or deep learning to be specific and doing some research on the subject, probably you’ve come across the term “neural network” in various resources. In this post, we’re going to explore which neural network model should be the best for temporal data.
Being a data analyst would mean you’ll have several skill-sets that one needs to work in the domain of data science. However, it doesn’t mean you can easily jump from your data analyst career into the role of a data scientist. Before discussing if being a data analyst could act as a step to becoming a data scientist, let’s take a look at what each of these professionals do.