Data analytics helps businesses find answers to the questions they need answered to increase their chances of success and long-term financial viability.
The availability of information and data has vastly increased over the years. Sorting through the massive amounts of data out there is something that only some businesses are up to taking on themselves. It is much less expensive and time-consuming to allow a qualified data analyst or analysis firm to handle all the information and statistics a company needs to address.
Companies can make better decisions in today’s challenging business world using analysis. Even small businesses find that using data can help them grow faster and be better prepared to meet challenges.
Here are some ways that data analytics and improved computer processing help businesses.
Companies can conduct surveys can collect data with greater ease.
In the past, conducting a survey and compiling the data was much more challenging. This was especially true if companies wanted to reach a wide customer base nationwide. Thanks to online surveys, it is much easier to reach out to customers and potential customers and gain valuable information that can be used to help make company-wide decisions and tailor products to meet consumer demand.
Data can be compiled into useful statistics using computer programs and analysis, rather than hand tallying, compiling, and record-keeping.
Parallel computing has allowed faster and more efficient data mining and analysis of computers.
Thanks to advancements in processors, computers can process and analyze amazing amounts of data in record time. Not long ago, it would have been impossible for data analysts to utilize the vast amounts of data available to businesses.
Now computers under the direction of skilled data analysts can process data at unprecedented rates. This allows businesses to utilize the most critical parts of the gathered data. These patterns can save countless hours and dollars when developing new products or considering if it is a good time to expand a company. There are countless other examples where analyzing large data sets and gleaning the most important information is helpful when it comes to making the best short- and long-term decisions.
Descriptive
Descriptive analytics helps companies see the big picture of what has happened and what is likely to occur at the company if they keep using the same strategies. Good examples of questions that descriptive analytics can answer include how much profit per customer, how many customers a business has, monthly and yearly revenue, and how ads are performing.
Diagnostic
These analytics help companies determine why something desirable or undesirable is happening. This helps companies find problems with system processes so they can create solutions to solve them.
Diagnostic analytics allow processes to be streamlined so operations run more efficiently. Diagnostic analytics may be used to make decisions involving any aspect of a business, from manufacturing to hiring.
Predictive
One of the most valuable types of analytics used by businesses is predictive. This type of analysis helps businesses make decisions by predicting the outcomes of those conclusions. By reducing risk, it is possible to avoid expensive or even disastrous decisions. This type of analysis can predict your business’s future if market conditions remain the same.
Analysts can also add other variables to predict the outcome if conditions change or your company makes a specific decision. Predictive analytics can help companies determine if a product is likely to succeed among specific demographics or what customers they are most likely to lose if they make a business decision.
Prescriptive
After a business has answered questions about how it reached its current point and where it is likely to be if market trends continue, it is logical to start using prescriptive analytics to decide the best choices for the future. For example, do you need to find different suppliers in order to cut expenses or production times? Is it worth developing a new product and launching it now, or is it better to wait until next year?
Cognitive
With cognitive analytics, companies can answer how they can improve in the future. This is great for long-term planning and creating realistic goals for teams.
Common applications for cognitive analytics include software that gathers information from a customer and then recommends a specific product based on their answers. At-home hair color companies are a good example. Cognitive analytics is why they offer potential customers a quiz to assess what product will work best for them based on their answers to questions about their appearance and the results they would ideally like to see.
What is the process of data analysis?
All data analysis follows a similar process, whether descriptive, diagnostic, predictive, prescriptive, or cognitive. By following a good process, data can be examined thoroughly, and analysts can make the best use of time.
Here is the process used to complete any data analysis project.
Identify the data
This is where you determine the exact type of data that you need to analyze. While it may seem easy to determine this, it is not always clear how much data you need to create a reasonable sample size for analysis nor where you need to collect your data.
At this point, you may realize you need to collect a lot of additional new data to accomplish your goals.
Collect data
There may be some data out there that you can use, but it may be better to collect your own or use both. Taking the time to get good data is critical. Data analysis is not worth your time if you do not have good data and data relevant to your company’s questions and goals.
Collecting data can take some time, but the good news is that computer programs make it easy to tabulate and see the raw results rather quickly. Online surveys and phone calls are the most common methods for collecting data. Texting surveys to people is another good method for reaching a lot of people at once.
Offering some incentive to get people to complete surveys can be helpful, particularly if you are polling previous customers. Something as simple as offering a code that can be used for one time discount on future purchases or offering a prize draw for those that complete the survey can increase responses a lot.
Cleaning data prevents misinterpreted results.
There is often some data that is an extreme outlier. It is beneficial to throw out this data because it can skew results too far in one direction and drastically alter the data’s average picture. Cleaning data may seem like it has the potential to change results dramatically, but the truth is the opposite. Extreme outliers can lead to missing the big-picture results entirely.
Analyze the cleaned data.
The level of analysis depends on the questions and information a company hopes to get. All five types of analysis may help a company create a plan for current and future operations and procedures.
Interpret the data.
This is the step where data analysts look for and find patterns that can be used to create models, graphs, and more. Multiple interpretations are often considered because companies ask many questions that depend on them making a specific decision.
Consider any future data analysis that needs to be done.
Doing some initial data analysis may highlight that additional questions must be answered. This can mean looking for patterns in the existing data or gathering additional data. In some cases, an entirely new set of data will need to be created.
For example, if a company decides to explore the potential for success of a new product among a different demographic than they usually cater to. This can help them decide without spending a lot of money and taking a risk.
Data analysts are in strong demand.
Many people earning their degree in computer science find that the demand for data analysts provides them with many lucrative job opportunities. Even smaller companies or those just getting their plans in order use data analysts. The difference is that smaller firms hire data analyst firms to take care of their data needs rather than hiring their own in-house team.
If you love to find solutions to problems and help businesses realize their true potential, now is a great time to pursue a degree in computer science. Not only will you learn more in-depth how data analytics help business, but you will also gain computer skills that open up many job opportunities. An MS in Business Analytics from St. Bonaventure University can be completed online while you maintain your current job. In under two years, you can be well on your way to a career in data analysis.
Data analysts are employed in many different industries.
Data analytics is helpful for any business. As an analyst, you can find a niche industry that you are passionate about or always had an interest in that you want to explore further. In some cases, those pursuing an advanced computer science degree have an undergraduate degree in an unrelated field, giving them unique and advanced knowledge that may be useful when working as an analyst in a particular industry. For example, a degree in biology would be useful for someone applying to be an analyst at a pharmaceutical or environmental company or service.
Some data analysts may specialize in specific areas, such as marketing analytics.
While many analysts study a wide range of data and answer all types of questions that companies might have, some are employed to specialize in an area of particular interest to a firm. Marketing analysts can offer a company many valuable skills and information that allow their marketing budget to be used most effectively.
By knowing your target demographic as well as possible, you can more readily tailor marketing campaigns to reach potential customers and increase customer loyalty.
Data analytics allow companies to streamline their operations.
Cutting back on inefficiencies within a company can be difficult. For starters, it can be hard to determine where inefficiencies occur at a larger or more complicated company. Let’s say that a company manufactures ten different products but seems to be experiencing a drop in revenue. Data analysis can help determine which products are decreasing in popularity and why. Perhaps a change in where the company is getting raw materials from has led to increased costs that are reducing profit margins significantly, or an alternative material source is not as high quality, so there has been a decrease in quality standards.
Data analytics can help protect companies from cyber-attacks.
Cybercrimes are on the rise. It is important to make sure that your customers’ information and data are safe from attack. Data breaches can lead to distrust and loss of your customer base.
Ransomware attacks are another serious issue. Taking a company’s operations hostage can cost a lot of time and money. This is why a lot of companies pay hackers the ransom they demand. Companies sometimes give in if the cost of not doing business exceeds the ransom. Of course, this encourages more crimes of this nature.
Analytics can determine where there are weak points in cyber security so companies can take steps to protect their information and computer systems. This is an investment well worth making in today’s business world.
Is data analysis the right career for you?
If you are considering changing your career path or finding a career that is interesting and in demand, consider computer science and data analysis.
Here are some of the key skills that indicate that you may truly enjoy the world of data analysis.
You are organized and punctual.
Data analysts need to stay organized and deliver their work on time. Businesses rely on punctual results and good organization to meet their goals and stay ahead of their competition.
Analysts that work for companies that do data analysis for many different businesses are often multi-tasking on different projects, so it is critical that they keep information and projects organized.
Sometimes, clients ask for more work on a tight deadline too. Analysts that can deliver work fast and accurately will go far in their careers.
Great communication and teamwork come naturally to you.
Data analysts have to work with many different people from all walks of life. They often have to collaborate with other analysts on larger projects too. Good written and spoken communication skills are essential to projects being accomplished with high accuracy and on time.
Analysts work with people from many different departments within a company to get the information and questions they need to answer to help the company achieve its goals.
You are curious and like to solve mysteries.
Data analysts are problem solvers. Data analysis may be a rewarding career choice if you are naturally curious and love a good mystery. Analysts are asked to find solutions and potential outcomes of obstacles that stand in the way of success, but they also uncover what is helping a business reach its goals.
Analyzing information and finding the most important trends can be like unveiling a great mystery with the potential for success.
You like math and working with numbers.
If you want to know the statistics of anything you are interested in, then data analysis may be just your job. Data analysts crunch many numbers to get companies the information they need.
Creating graphs based on numbers and extrapolating them to show businesses what results they might expect to see if they make specific choices is incredibly helpful to them when planning their operations for the future.
Flexibility and the room to grow are desirable to you.
With a degree and career in data analytics or computer science, you can choose to work at many different companies. While you may start working for a larger company specializing in data analysis, you may go on to have your own company or take on a full-time role for a single company.
Over the years, you may decide that you would like to work in a specific industry. All of these options are open to you throughout your career. Analysis jobs can allow you the flexibility to relocate to many different locations or even work from home if that is appealing to you.
Conclusion
Data analytics help businesses predict how decisions will affect their future so they can make smart business decisions. Data can tell a business a lot about what its customers want and need so businesses can concentrate on developing and marketing the products, most likely to give them a positive return on their investment.
Data analysis allows companies to gain information to remain competitive during challenging market conditions.
