What is the difference between data analytics and machine learning?

The terms data analytics and machine learning get used a lot. This post will help show you what the terms mean and how they relate to each other.

So, what is the difference between data analytics and machine learning? Data analysts collect data, analyze it and explain the results to help make business decisions. Machine learning is where computers are able to learn from data and make predictions based on the data without being explicitly told how to.

The roles of a data analyst certain jobs in machine learning such as data science will often share similarities and many of the skills that they require will be the same. However, there are a number of key differences in other skills that they have, their backgrounds and what they do on a day to day basis.

Data analytics

The main role of a data analyst is to collect data, analyze the data often in the form of graphs and to use the data to help make business decisions.

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You can watch the video below to see what a data analyst does and how it differs to other types of job roles.

How much they get paid

According to Glassdoor, the average annual salary of a data analyst is $67,377.

However, the location and your level of experience will have a large impact on the amount that you would likely receive.

According to payscale, the 10th percentile of data analysts receive $41,000 and the 90th percentile of data analysts receive $83,000.

Background and skills of a data analyst

The main skills that a data analyst will need to have are strong proficiency in SQL, Microsoft Excel, Python or R, data visualization and a good understanding of statistics.

Data analysts will normally have a bachelors degree in a field such as mathematics, statistics, marketing, finance or computer science.

How to become a data analyst

To become a data analyst it would normally be necessary to have a bachelors degree.

However, there are some data analyst boot camps that are designed as intensive courses that take place over the course of a few months that will often help you with getting a job afterward.

The main thing that will help you in getting a job as a data analyst is the ability to show that you have relevant experience as a data analyst. The best way to do this would be to get data analyst internships while doing a bachelors degree.

Other ways to show that you have relevant experience would be to do data analytics projects. You could do the projects by acquiring and analyzing datasets yourself or you could do the projects that they give you on websites such as Dataquest or Udacity.

Is machine learning required to become a data analyst?

Machine learning is not generally required to be a data analyst. If machine learning is a part of the data analysts job then it would make it data science.

A data scientist is similar to a data analyst but a data scientist will apply predictive machine learning models to the data. The models will be designed to do things such as recommend products to people, predict the optimum way to place ads on a website or to make other predictions.

Machine learning

In recent years, there has been a sudden and dramatic increase in the amount of data that businesses and other organizations have available to them.

The task of machine learning is to derive meaning from this data by doing things such as making predictions and finding patterns, within the data, that humans wouldn’t normally be able to spot. The machine learning algorithms that are used to do this can do so without being explicitly told how and they will amend the predictions that they make when new data is made available to them.

There are many machine learning algorithms that are used to do this and they can be computationally expensive. Previously, computers were not powerful enough to run the machine learning algorithms but computers have gotten powerful enough in recent years to make full use of them.

You can watch the video below to see what machine learning is.

Types of jobs in machine learning

There are a number of different types of jobs that you can get in machine learning.

One of the most popular ones is that of the data scientist. A data scientist will gather, process and apply machine learning models to data. Their primary job will usually to help businesses make better decisions using data.

Another type of machine learning job is that of the machine learning engineer. The job of the machine learning engineer will generally be to make machine learning models and to put them into production so that they work alongside all of the other functions of the business. Sometimes, the role of a machine learning engineer will be to take machine learning models made by data scientists and to put those into production at scale.

Another type of machine learning job is that of the research scientist. The job of a machine learning research scientist will be to develop and maintain the machine learning infrastructure of a business. To be a research scientist it will often be necessary to have a Phd in a quantitative field.

How much machine learning jobs tend to pay

According to Payscale, the median pay of a data scientist is $91,000, the 10th percentile make $62,000 and the 90th percentile make $131,000.

According to Payscale, the median pay of a machine learning engineer is $110,000, the 10th percentile make $76,000 and the 90th percentile make $152,000.

According to Payscale, a machine learning research scientist has a median pay of $119,000 the 10th percentile make $70,000 and the 90th percentile make $163,000.

One reason that the pay of a data scientist might appear to be lower than the other two could be that many data analytics positions are often posted as data science positions.

Skills and background required for machine learning

To get a job in machine learning it will be necessary to have a good understanding of calculus, linear algebra, probability, statistics, programming, data analysis and of databases.

A machine learning engineer will usually have a masters degree in a quantitative field such as mathematics, computer science or statistics.

If you need to learn the skills necessary to get a machine learning job then here are some of my suggestions:

Calculus (MIT)

Probability (MIT)

Linear algebra (The University of Texas at Austin)

Machine learning (Andrew Ng, Stanford), Deep learning and machine learning (MIT)

Data analysis (Data School’s channel on Youtube)

Getting a job in machine learning

To get a job in machine learning it will usually be necessary to have a masters degree in a quantitative field. However, you might be able to get a job as a data scientist with just a bachelors degree if you can also show that you have experience in other ways as well.

While doing the bachelors and masters degree it would be helpful to do internships as these will usually be very helpful in getting a job either directly with the company or by showing that you have relevant experience.

Other ways that you can show that you have relevant experience would be to do projects of your own, compete in machine learning competitions, go to machine learning hackathons, contribute to open source or to make your own blog or youtube channel.

I have written, in more detail, in the past about how you can go about getting relevant experience for machine learning jobs here.