Data analytics is a way of looking at data to determine a pattern and trend. It uses unique methods like statistical analysis and machine learning to cover interpretation from data. Data analytics has become increasingly important as a result of the emergence of big data.
Data Analytics aims at collecting data and using various techniques to bring out various information from the data. Some of the techniques that are commonly used include data mining, machine learning, statistical analysis, and data visualization. Data analytics is applied in different organisation/industries e.g., Retail, Healthcare, Finance, Marketing, Telecom, etc.
Importance of Data Analytics
As the world has moved into a global village with the help of Information technologies (IT), the importance of data analytics cannot be overemphasised.
The following are some of the importance of data analytics.
- Effective Decision Making: Data analytics aid organisations in reaching decisions that are made based on facts. Organisations can also find patterns and trends with the application of data analytics. It can also support the process of optimisation, cost reduction and revenue growth in an organisation.
- Management of Risk: Data analytics can assist businesses to identify and reduce risk in form of fraud or cybersecurity concerns. Organisations may pinpoint trends and irregularities in data that may be dangerous, and action will be taken before it becomes too late.
- Support Better Understanding of Customers: Data analytics helps the organisation understand its clients’ behaviour, with aim to provide customised customer service experience.
- Competitive Advantage: Data analytics can help a business to see opportunities that its competitors may not have seen thereby giving them an edge over them.
- Strengthen Efficiency: By identifying operational inefficiencies using data analytics, businesses can better implement adjustments that can result in time and resource savings. Hence production and profitability will increase.
Limitations of Data Analytics.
Data Analytics may not be said to be accurate all the time as it has some limitations. The following are some of the limitations of data analytics
- Improper Interpretation of Data: sometimes data may not be interpreted accurately thereby giving misleading result that would adversely affect decision making.
- Privacy Laws: Sensitive data in terms of medical records of a patient, and personal finance transactions cannot be put in the hands of someone who cannot secure it.
- Data Quality: Inaccurate data can jeopardise decision making.
Data Analytics and Business Growth
Analytics can undoubtedly help a firm expand by giving useful insights into important business KPIs and by assisting in the identification of opportunities and areas for improvement. Businesses can better understand customer behaviour. Market trends, operational efficiency, and other aspects by utilising data analysis tools and procedures
Data Analysis can also assist a company to identify the products or services that are most profitable to them. It can also be used to analyse customers reviews as a way of feedback.
Conclusion
Organisations may make better judgements and take actions that would bring about growth and increase in profit. It is important to note that analytics is simply one tool among many that companies may use to enhance operations and accomplishment of the business objective.
Analytics is not a magic bullet for a company’s success. It is crucial to approach analytics as a component of a larger strategy framework that considered the requirement and difficulties faced by firms.