Data is the foundation for making well-rounded decisions. Everybody makes choices. However, business owners and professionals can make critical decisions that will lead to the desired outcome.
Although accurate business data is not guaranteed to yield a positive outcome, it can help them make better decisions. With advancements in Data Science and data visualization, organizations can now collect and analyze data in many different ways. This makes it easier to solve problems.
Business analytics could be for you if data is your passion or you love finding answers to specific questions. What is business analytics? What are its purpose and benefits? What are its main benefits and applications? These are just some of the questions we will answer.
Business analytics is an exciting field with many opportunities. Learning more about it could open the door to a new career as a business analyst. The online Master of Science program in Management Information Systems can help you prepare for this career. It will equip you with the skills and knowledge to reach your professional goals while keeping your job.
What is Business Analytics?
Business analytics is the process and procedures organizations use to make better decisions. These methods and procedures can include statistical methods, predictive analytics, programming languages, as well as modeling, and machine learning. These methodologies are all state-of-the-art thanks to technological advancements.
Data is everywhere. Through the use of smart devices and consumer electronics, huge amounts of data are generated every day. Many of these data are easily accessible. This is where business analytics comes in. It involves obtaining the raw data, then analyzing it mathematically and statistically, and finally applying the results to solve problems or find solutions.
Also read: What is Financial Analytics A full Guide?
U.S. News & World Report speaks with Douglas Laney, West Monroe’s innovation fellow for data analytics strategy. News & World Report says this is the golden age for data science. It would be a smart move for business owners to make use of it.
Monroe warns that the data world is very extreme and companies who do not use it effectively can be put in a competitive hole.” “[Business analytics] is about using data to create insights.”
Analytics, also known as statistical analysis, is the computation of data in different forms. Analytics can be divided into three main categories:
- Descriptive data
- Predictive analytics
- Prescriptive analytics
Their descriptor is what defines their type. Descriptive analytics can be described as statistics that attempt to describe events and actions. One classic example of descriptive analysis is key performance indicators. Because descriptive analytics is based on historical data, business analysts may use descriptive analytics to make conclusions about financial problems in an organization.
When decision-makers need to know what might happen, they can use predictive analytics. This is done by looking for patterns or similarities in data. Historical data can also be used here, but it is parsed and fed into predictive algorithms to give an idea of what might become. A retailer or salesperson may want to advertise a product but aren’t sure which medium or method will work best. For example, a TV advertisement or an online banner. They can use predictive analytics to determine which channel has resonated most with buyers. Predictive analytics also includes machine learning.
Prescriptive analytics is a mix of descriptive and predictive analytics. Historical data is used here to predict recurring outcomes.
If a franchisee or restaurateur is trying to figure out how much produce they need for the weekend rush, they might look at past receipts or go through inventory from past weekends. They may see patterns and repeat them if they can recognize them. Prescriptive analytics can be used to plan capacity and allocate products.
These methods allow business owners to analyze data effectively so that they can make informed decisions.
What is Business Analytics Tools?
Business analytics can be used as an independent tool. However, in order to interpret and make use of the data, businesses will need specific tools or equipment. Software is one type of business analytics tool. Spreadsheets are one of the most basic types. Spreadsheets often include statistical methods and functions that can be applied to data so it is easier to understand and extrapolate. Business intelligence tools are able to not only aggregate data but also perform functions that allow data to be used in business decisions.
Enterprise resource planning software is a powerful tool for business analysis that many companies use to improve visibility into their work processes. These and similar systems are being tapped by organizations. Mordor Intelligence asserts that the business intelligence industry is multibillion-dollar and will be worth $40 billion by 2026. This is an increase from $20 billion in 2020.
Business intelligence systems and methods, which include predictive models, programming languages, data mining, and data mining, are changing the way people manage their businesses to grow, prosper, and improve. They are using them regularly. Logi Analytics polled the knowledge workers (e.g. physicians, programmers, engineers, scientists, etc.) Analytics is a discipline that averages five hours per day. Nearly all respondents (99%) said analytics was valuable in helping them make better decisions.
New ways to analyze and collect data are possible, given the industry’s rapid expansion. This is partly due to technological innovation. Laney points out that what is considered the current state of the art may soon be outdated.
Laney told U.S News & World Report that “I would not encourage anyone gets fixated upon any type of technology because it’ll be secondary in two or three years.”
This topic is covered in greater detail in the three-credit course EmergingIT Trends & Tech. It is part of UAB’s Management Information Systems core.
What can Business Analytics be Applied?
Business analytics is perhaps the most important aspect of this field of data science. It is universally usable. Business analytics can be used in any sector. If the solution isn’t being used by business owners, they hire someone to do it. Here are some examples:
Social media, whether it’s Facebook, Twitter, or TikTok, would likely not be as popular, nor the way it is today if it weren’t for analytics. Many people log onto their accounts to communicate with family and friends, but they also use social media to gather news. Gallup’s recent survey shows that nearly three-quarters of 2020 respondents used social media to stay connected during the pandemic. Furthermore, 68% of respondents said that they found it useful for keeping up to date with news organizations and 70% claimed it allowed them to get guidance from officials.
Data analytics is an important factor in determining what information and posts users see in their news feeds. Data analytics plays a significant role in the stories that appear on your screen. Social media managers use predictive and prescriptive analytics to predict what their users are most likely to click on, based on past choices.
These analytics can be used by businesses who want to advertise on social networks to identify their target audience.
Marketing firms also use business analytics in a similar fashion. Marketing firms can use business analytics to determine which campaigns are most popular and guide future advertising strategies.
Every day, huge amounts of energy are used to power daily activities, from the gasoline motorists use to fill their cars with, to the kerosene they use to heat their homes. To avoid shortfalls and surpluses, oil and gas producers must make frequent decisions about how much fuel they have on hand. Prescriptive analytics may be used by producers to make judgments about prices or extractive activities.
Manufacturers must manage their supply chain, no matter what product they produce. This is something that professionals in the industry know for a long time. However, this was made more apparent to consumers during the COVID-19 pandemic. During this period, products such as paper and sanitizing products, which are usually easy to find, became difficult to find.
Due to the unusual nature of the coronavirus epidemic, there were many disruptions and breakdowns in the supply chain. Manufacturing decisions are affected by inventory, downtime, maintenance, and other variables. Forecasting metrics and methods are used by business analysts to help manufacturers have a predictable supply chain.
Business analytics is available in any sector. This could explain why business analysts are a fast-growing occupation. According to the U.S. Bureau of Labor Statistics (USBS), the number of jobs will increase by 11% between 2019-2029. All occupations have a 4% average growth rate.
What are the Challenges in Business Analytics?
Data analytics can be a powerful tool for empowering decision-makers to make better business decisions, as the Logi Analytics survey shows. It’s not perfect, however. These are just a few, and some are covered in the master’s program curriculum.
It is almost impossible to comprehend the sheer amount of data being recorded. Tech Jury reports that humans alone generate 2.5 quintillion bits of data each day. It can lead to information overload, or possibly the wrong type of data.
In the future, automation may be used to ensure that data systems collect the correct type and amount.
Without someone to use it or analyze it, data is useless. It is possible for data to be misinterpreted, or used in a way that isn’t consistent with its intended meaning.
Automation may also be useful in this area to prevent communication breakdowns and ensure that decisions are not based on incorrect analysis or interpretation.
Poor Data Quality
Good decisions must be rooted in sound data and intelligence-gathering practices. Bad data can lead to incorrect conclusions. These errors could have been caused by simple human error, such as when data was entered or analyzed incorrectly. Real-time data is best for evaluating data, and outdated data could be another indicator of poor data quality.
Data that is Difficult to Access
Although data is everywhere, it can be difficult to access or even obtainable. This could be because of poor collection methods, obsolete legacy software systems, and logistical problems.
Data accessibility is becoming easier and more labor-intensive thanks to cloud computing, enterprise resource management software, centralized database systems, and other data collection methods. These practices will only get easier as technology advances and improves. However, they will require robust data security measures to ensure that sensitive or privileged information is not lost.
Also read: Data Analyst: What it is and How It’s Work
What are the Biggest Successes of Data Analytics?
Although no data collection strategy or science can be perfected, analytics has had just as many successes for each challenge it faced. Analytics can accurately predict business outcomes and enable organizations to make better decisions. Without providing more opportunities for growth and improvement, analytics could be abandoned.