Business analytics is everywhere. Even businesses that are not actively doing business analytics do some form of it without knowing it. Business analytics uses data to provide business insights. This is done through the proper collection and analysis of this data to come up with actionable objectives. Business analytics also determines which sets of data are important, discarding those which are not and trying to find ways in which the data can be used to solve business problems as well as increase efficiency.

Business Analytics’ Focus

The main focus of business analytics is providing actionable data. When doing this, business analysts focus on the methods used to analyze data, recognize patterns, and create models that can be used to understand past events and predict future ones. The conclusions gained from this exercise can then be used to streamline outcomes.

Business analysts use:

• Quantitative analysis
• Mathematical models
• Sophisticated data

All three of these are used together to come up with solutions that require data-driven solutions. Business analysts also use artificial intelligence, neural networks, complex data sets, and neural networks to segment the data available to them and identify patterns with this data. These patterns can then be used to predict future events, market trends and nudge customers towards a desired marketing goal.

The Technology Behind Business Analytics

Business analytics uses technology heavily to analyze data. This technology is usually in the form of programming languages such as:

• R
• Python

These programming languages are chosen specifically because they are flexible enough to fit a wide variety of use cases as well as being powerful enough to handle the computational tasks business analysts need. The biggest advantage of using these programming languages is that they both have large communities backing them. This large community is also responsible for the iterative improvement of the tools built using these programming languages. This means that a business analyst’s work gets easier every year.

If you want to be able to use these programming languages, you need programming skills. Luckily, many analytics masters online programs, such as the one provided by Suffolk University Online, teach students how to use them and create their own analytics models using these programming languages.

Business analysts who do not have a programming background can use statistical analytics tools that have a graphical user interface. These tools are generally quite expensive but they make an analyst’s job easier.

Benefits of Business Analytics

Business analytics has a number of benefits including:

• Helping businesses plan for the future. Businesses do not have to guess what will happen in the future because business analytics tools have become so complex that predicting future events is now done very accurately
• Business analytics can help businesses make data-driven decisions which can lead to increased profits and improved efficiency
• Business analytics can help create new types of marketing strategies. The data collected and analyzed by business analytics tools can help businesses better understand their customers’ behavior. This makes it easier for businesses to target these customers with customized marketing campaigns that often have better outcomes than traditional marketing efforts.
• Business analytics can help improve customer retention. By understanding customer habits, businesses can find different ways to tailor their services to these customers thereby helping retain them
• Business analytics can help businesses cut losses. It can help a business know when its low season is going to be. The business can then cut down on production in preparation for the predicted fall in sales. This ensures a business is not left with dead stock which can lead to huge warehousing and storage expenses.

Business analytics Components

Business analytics has different components:

• Data aggregation – Data has to be collected, categorized, and checked for duplicates before it can be analyzed. Data aggregation can also help filter out incomplete, inaccurate or unusable data. Data can be collected from transactional records such as sales, shipping and bank records as well as from volunteer data. This is data supplied by customers on a website or other platforms. Volunteer data is usually personal data so it should be handled with care.
• Data mining – Data mining is primarily done to uncover unrecognized trends and patterns. Models can be used to mine data for these purposes. Data mining uses include the following:

1. Classification using demographics such as age and gender to sort data
2. Clustering, the act of identifying patterns to know what variables exist when the data set is incomplete
3. Regression, the use of models to predict numerical values based on past patterns

• Text mining – Business analytics tools can also collect textual data from a variety of sources including blog comments and social media websites. This textual data can be used to improve existing products, create new products and product categories, as well as review competitor performance.
• Predictive analytics – Businesses can use models to predict issues such as:

1. Equipment breakdown based on prevailing environmental factors
2. Market trends, even event-related or seasonal spikes and falls in demand

• Data visualization – Data analyzed using business analytics tools can be plotted on graphs to see how well a model is working, explore new areas to analyze as well as make statistical predictions.
• Forecasting – This is the prediction of future events based on factors such as retail sales, energy demands or a spike in internet searches. Forecasting is based on historical data so it is deemed to be very accurate.

Collecting Data Ethically

As mentioned, business analytics needs data to analyze and extrapolate from. One of the biggest pitfalls a business can fall into is not collecting this data ethically and taking care of it so that it does not fall in the wrong hands. Users have to know you are collecting their data if they are on your website. This can be done using disclosures and privacy policy pages. If you are data mining, ensure that you do not collect user-identifiable data. If you do, you need to get rid of it as soon as you are done analyzing it.

Finally, ensure the system you use to store the data is secure so as to protect user-identifiable data.

Almost all businesses collect data, but it is what they do with this data that matters. Data can help shape a business’s future and it is therefore important that every business has a data analytics system in place to make this data work for them.