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Business Analytics Overview

As technology has become more sophisticated in the last decade, business analytics is everywhere today. If you are interested in a dynamic career in business and technology, it is wise to learn all about it because it will become even more important in all sectors of the economy in the coming decades.

Business analytics involves the collating, sorting, processing, and studying of business data. It uses iterative methodologies and statistical models to transform large amounts of data into information that can be used to make business decisions. The primary goal of business analytics is to decide which datasets are important and how they can be used to solve business problems, increase profits, efficiency, and productivity. (Microstrategy.com)

Business analytics is a subspeciality of business intelligence and is implemented by highly skilled professionals with the goal of identifying data that can be used to make business decisions. Business intelligence is usually focused on tools and strategies used to acquire, identify and categorize raw data to report on current or past events.

Business analytics, on the other hand, is dedicated to the methodology by which large amounts of data can be analyzed and patterns identified. It also is intended to develop models to bring more meaning to past events, create predictions for events in the future, and recommend business actions to maximize profits.

Professionals with a master’s degree in business analytics use sophisticated data, quantitative analysis, and mathematical models to create solutions for data-driven business problems. Business analytics professionals use information systems, statistics, computer science, and operations research to expand their knowledge of complex data sets. They also utilize artificial intelligence, deep learning, and neural networks to break down large datasets and identify important patterns. This information is then leveraged to predict events in the future that are related to consumers and market trends.

Job Demand Rising in Business Analytics

With all of the data that companies have access to today, job demand in business analytics will continue to rise quickly. For example, business analytics professionals often work as management analysts, which will see a 14% rise in job demand by 2028, which is much faster than average. (Floridatechonline.com)

High Salaries With a Business Analytics Degree

Professionals with a background in business analytics can anticipate earning high salaries for years in the future. For example, the Bureau of Labor Statistics reports the median salary for financial analysts using business analytics is $85,600 with a range of $52,500-$167,400.

Workers with a master’s in business analytics will be able to earn more than $100,000 per year in most cases Top industries for financial analysts with a business analytics background are: (BLS.gov)

  • Securities, commodity contracts and other financial investments: $101,400
  • Professional, scientific, and technical services: $84,500
  • Management of companies and enterprises: $83,600
  • Credit intermediation and related activities: $81,400
  • Insurance carriers and related activities: $78,800

Also, Payscale.com reports the average salary for an analytics manager is $94,677 with a range between $67,000 and $126,000. (Payscale.com)

Some listed salaries with specific companies include:

  • P. Morgan Chase: $109,000
  • Expedia: $110,000
  • Merkle: $119,000
  • Accenture: $115,000
  • Synchrony Financial: $82,000

Your salary will rise as you gain experience in business analytics; Payscale.com reports career salaries based on experience ranging from $71,000 in year 1 to $114,000 in year 19.

What You Learn in A Master’s in Business Analytics Program

Master’s in business analytics programs will vary in their content, but the essential concepts of business analytics that you will learn include:

Data Aggregation

Before data is analyzed, it is necessary to collect, centralize and clean it to avoid duplication. It also needs to be cleaned of inaccurate, incomplete, and unusable data. Data can be aggregated with the following:

  • Transactional records: Part of large datasets that are shared by a company or a third party, such as sales records, banking records, and shipping records.
  • Volunteered data: Supplied in digital or paper format that is provided by the consumer directly or by a third party. It is usually personal information.

Data Mining

To reveal and identify trends and patterns that have not been recognized, a business analytics professional can create models by mining large amounts of data. Data mining uses various statistical methods to reach clarity:

  • Classification: For when important variables are known, such as demographics, and can be used to sort and group the large amounts of data.
  • Regression: Used to make predictions about continuous numeric values. It is based on extrapolating historical patterns.
  • Clustering: Used when factors needed to group data by class are unavailable. Patterns need to be identified to figure out the variables that exist.

Association and Sequence Identification

Consumers can do similar actions at the same time or do predictable actions one after the other. The data can uncover the following patterns:

  • Association: Two different products that are often purchased at the same time, such as several books in a series or a toothbrush and mouthwash.
  • Sequencing: A consumer might request a credit score report and then a loan. Or, they might book a flight online and follow that by reserving a car.

Text Mining

Organizations also can gather textual information from blog comments, social media websites, and call center scripts to obtain relationship indicators. The data is used to:

  • Develop in-demand products
  • Enhance customer service and experience
  • Review competitor performance

Forecasting

Forecasting is foreseeing future behaviors or events based on past data. It can be created by doing process analysis for a specific season or period. Some examples:

  • Demands for energy in a city with a stable population in a particular month.
  • Retail sales for a certain month, such as the biggest sales days.
  • Increases in Internet searches for a certain event that recurs, such as the Olympics

Optimization

Companies can find best-case scenarios and next best actions by creating simulation techniques, such as:

  • Pricing for peak sales and using spikes in demand to boost production as needed and keep steady revenue.
  • Shipping and stocking options for inventory that optimize delivery schedules and satisfaction among customers without reducing warehouse space.

Predictive Analytics

Organizations can use predictive scoring to deal with the following events:

  • Gain and loss of customers that is narrowed down to an age bracket, income, etc.
  • Failure of equipment during times of heavy use
  • Market trends, such as transactions that take place only online

Summary

The business analytics field is growing, and so are job opportunities and salaries. Earning your master’s degree in business analytics is a great move for your future! Learn more on this website about the business analytics field and education, and contact MasterofBusinessAnalytics.com if you have any questions.

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