Data Science Blog – Page 8 – Magnimind Academy

13
Sep

What Are The Basic Requirements For A Data Analyst Or A Data Scientist?

If you’re trying to step into the data science field and have gone through any job portal, most likely you’ve observed that both data scientist and data analyst job positions are in high demand with impressive salaries. While both these positions share some similarities, there’re significant differences in terms of basic requirements understanding which is necessary to select a path to follow. In this post, we’ve outlined the fundamental requirements for both data scientist and data analyst positions to help you make an informed decision.

13
Sep

Is It Easy For Data Engineer To Become Data Scientist?

These days, the business world runs entirely on data and none of the companies can survive without data-driven strategic plans and decision making. The field of data science is quite broad and contains a significant number of job positions including data scientist and data engineer. If you want to step into the data science field, it’s crucial to understand the differences between a data scientist and data engineer to identify whether it’d be possible for you switch positions without investing much effort and time.

13
Sep

How We Use Big Data Analytics Tools?

While the concept of big data isn’t new, most businesses have recently realized that if they can capture all the data which streams into their operations, analytics can be applied and significant value can be derived from that. Now, the massive amounts of data only become useful when big data analytics is performed to identify patterns and insights that would be left undiscovered otherwise. As a result, businesses are increasingly looking for professionals who’re familiar with various big data analytics tools to get help in attaining their goals. Here’s an overview of some popular big data analytics tools.

13
Sep

What Are Real-life Examples Of The Application Of Big Data Analytics?

These days, as the world is getting more and more connected through different types of digital devices, a massive volume of data is getting emanated from a huge number of digital sources. Businesses and organizations from across the globe are leveraging the power of this data and putting it to their advantages. Big data analytics is performed to identify correlations, hidden patterns, and to derive actionable insights that can help businesses make informed decisions.

13
Sep

7 Awesome Difference Between Data Science Vs Data Mining

As organizations and businesses have started to realize that there’s a huge value hiding in the massive amount of data they capture on a regular basis, they’ve been trying to employ different techniques to realize that value. While the ultimate goal is to produce actionable insights from that data, the tech world is getting filled with a significant number of technical terms. And among all these terms, probably the most talked-about terms are data science and data mining. Though some people use them interchangeably, they come with significant differences. Here’re seven most prominent differences between data science and data mining.

13
Sep

What Exactly Does Data Science Mean? Is It Really Going To Revolutionize The Industry?

You’ve probably heard the fact that the role of data scientists has been declared as the hottest job of the 21st century. If you’re not much interested in knowing about the latest advancements or buzzing technologies that are taking the tech world by storm, it’s quite normal to wonder why businesses, regardless of their volume and industry, are emphasizing so much to hire these data science professionals. In this post, we’re going to learn what data science actually stands for and how it can benefit the industry.

10
Aug

How Do You Build A Data Science Portfolio?

There’re a lot of people trying to step into the field of data science. Unfortunately, many of them often overlook one of the most critical aspects of landing up a good job in the field – the importance of building a strong data science portfolio. While having enough knowledge about different data science techniques and a good number of certifications are surely critical, unless you have a strong data science portfolio, your chances of coming under the radar of recruiters aren’t extremely high. Here, we’ve jotted down the key aspects of building a solid data science portfolio that would make your journey a tad easier.

10
Aug

The Most Powerful Idea In Data Science

In the tech fields these days, there’re a huge number of people trying to embark on different types of new paths that eventually lead to having a career in the field of data science. Undeniably, the goal is a worthy one, but it’s also important to have a clear idea about the key goal of data science. In this post, we’ll be trying to explore it. Let’s start the discussion.

10
Aug

What Are The Advantages And Disadvantages Of Big Data?

In today’s business landscape, big data has become the most valuable asset for any business. The more a business can harness big data, the better its position becomes from where it can carry out analysis that helps to develop useful business decisions. Across every industry, big data is being heavily used to predict future trends, recognize patterns, and draw new conclusions. However, like every technological advancement, big data also comes with equal shares of advantages and disadvantages. Let’s have a look at them.

10
Aug

What Tools Do You Use To Perform Data Analysis?

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.

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