Business Analytics

Businesses worldwide need to improve their quality to avoid being. They must follow trends, improve efficiency, and optimize overall performance. In doing so, this is where business analytics is needed. Business analytics analyses data into insights to improve business decision-making for better outcomes. They measure performance and drive growth in a business. By analyzing the data in a business, they help discover hidden trends, generate leads, and scale the business in the right direction. Business analytics also help solve a business’s lack of understanding and poor communication. The business analysis process first defines the current situation and the business’s goals. The second is to analyze the data, where the what, who, when, how, and why questions are asked from the data. In this part, business analytics has three methods: descriptive, predictive, and prescriptive. The last part is to decide on the business’ next step after analyzing the data using the business analytics tools. 

Collecting data is the primary source and the backbone of a business analytics process. Business analytics need as much information and data as possible to be processed and analyzed correctly. Like any other process, some problems and risks come with it. It also applies to the business analytics process. In collecting data, businesses have the most trouble processing & analyzing data, protecting data privacy, and ensuring data accuracy. These are the main issues of business analytics, they give excellent outcomes in the long run, but some matters need more attention to avoid unwanted problems from happening.  

It can be concluded that the more data that is collected, the more volume of storage that is needed. In this case, the scale is much bigger, not just the volume of the database, but also the variety and the velocity of the data that increases. This situation can cause the analytics process to drop and separate data more challenging. The enormous amount of information received also means tons of irrelevant, unimportant, inaccurate, and incomplete data sets in the system. An advanced analytical tool is very much needed to analyze and sort essential data in a sea of information. Analyzing and processing data would take so much time if done manually without the help of technology. A flexible information system that focuses on updating the system with the latest innovations and can sort data into meaningful order or groups is a way to avoid incorrect data analysis and observations.       

After the company managed to sort the enormous amount of information, the next thing they need to ensure is the information’s validity. That is another problem in the business analytics process. According to an Experian study, up to 75% of businesses believe their customer contact records contain inaccurate data. Data validation and accuracy is a time-consuming process, especially if it is done manually. It threatens the analytics process because data could be outdated, low quality, and fake. A company must ensure that the data are complete and true to make decisions based on accurate and factual information. Because no matter how well the analysis process is, if the data is not accurate or authentic, all the analytics activities will be ineffective or very harmful to the business. In fighting this issue, data validation by scripts and programs works effectively. This process uses a scripting language such as Phyton to write a script for the data validation process. Data validation involves comparing sources and searching for inconsistencies, incorrect formats, and null field values.  

The amount of important information stored in a database is undoubtedly alluring to hackers and business rivals. They will find all sorts of ways to steal information that they want. Data security and privacy are another challenge as the volume of data stored in the database increases. The leakage of important information can lead to financial losses and even the liquidation of companies. It can end badly for the business. In maintaining the data from getting hacked, businesses need to step up their security measures; they need a solution that automatically traces data lineage to know the source of the data. Besides that, building advanced technology in the system is essential to mitigate the threats. It should encrypt data with secured login credentials, record audit logs, conduct training on data, and alerts the right people if something goes wrong. Hiring a cybersecurity professional can be a faster alternative to help monitor and protect the database from unwanted crimes.   

Lastly, managerial plays a massive role in business analytics because not only does a system sort, record, and predict data patterns but s, but human skill is also needed to make the final decision from all the given data. Managerial is essential because they need to understand business analytics since their decision-making profession arises from this process. It leads to another problem, which is a talent shortage. Based on an EMC survey, their study revealed that 65% of businesses predict that they will see a talent shortage within the next five years. Their threat is the lack of workers with existing data science skills or access to training. Workers with hard skills are in less demand since machines have slowly replaced them; on the contrary, the demand for workers with soft skills in understanding how to program, repair and apply new solutions is increasing in this era. Hence, it makes them hard to find. A few solutions can fix this problem: investing in training programs that connect learning with on-the-job experience, developing mentorship programs, researching new ways to develop talents through certificate programs and online courses, and providing many learning opportunities for people to develop their soft skills. 

The business analytics process is one of the most essential parts of a business because it helps it develop and thrive in a world of competitors. Nevertheless, this also comes with a price; with the primary process of collecting essential data, the following risks and threats are also huge. Consequently, better system operations and protections are needed to keep the business from incoming threats. Businesses need to develop more advanced technology to ease business analytics processes, like having an extensive and neat database, an automated data validation and accuracy process, and safe and secured data security. Another solution that can help ease the process is providing people with more soft skills training opportunities. It can also be a benefit to businesses because it will help lessen the shortage of talent. This way, analyzing and processing data to improve a business will be easier and will help develop the business much faster without having as much worry about the threats and risks that follow.  

References: 

• https://getonline.uwf.edu/business-programs/mba/managers-understand-analytics/  
• https://www.3pillarglobal.com/insights/current-issues-and-challenges-in-big-data-analytics/  
• https://whataftercollege.com/business-analytics/challenges-in-business-analytics/  
• https://www.batimes.com/articles/10-common-problems-business-analysts-help-solve/  
• https://www.pathstream.com/data-analysis-challenges/  
• https://hevodata.com/learn/data-validation/