Data analytics is a broad term that encompasses different processes and techniques of data analysis used to understand raw data and gain inferences to improve things. Data analytics solutions can reveal metrics and trends that are otherwise lost in heaps of information.
These insights can then be utilized to optimize and streamline workflows and processes, to ultimately enhance the overall efficiency of any business system. Many data analytics techniques and processes have been automated into mechanical processes or algorithms, making it more convenient to convert raw data into a form that is easy to understand and analyze.
By incorporating data analytics into the business model, companies can reduce costs by identifying more efficient ways to conduct different processes and by storing large amounts of data in a single, comprehensive location.
Data analytics can also be used to make better, more informed decisions, and help understand customer trends and satisfaction, leading to improved and more satisfactory products and services.
It can be broadly classified into four types – predictive, descriptive, diagnostic, and prescriptive analytics, based on the specific purpose that the analysis process is supposed to achieve. The applications of data analytics are prominent across several sectors, including finance, healthcare, crime prevention, and environmental protection, to name a few.
The COVID-19 pandemic disrupted a lot of things, from the supply chain to consumer behavior. Data analytics solutions adapted to this change, even though the unpredictable nature of the pandemic was quite challenging.
Many companies utilized descriptive analysis tools to rapidly analyze data about the past and present, and gear up for the future. With more and more data being collected every day, the potential applications of data analytics are endless, in science, business, and even everyday life.