Big data now plays a crucial role in every business’ success. Through the application of analytics, data analysis is allowing businesses to become even more competitive.
Organizations adopt big data and analytics to analyze massive volumes of data generated by offline and online trading. Based on the Big Data & Business Analytics Market Statistics 2030, the value of the global big data and business analytics market is estimated to increase to $684.12 billion by 2030 from $198.08 billion in 2020.
The goal of data analysis is to extract meaningful information and use it to make informed business decisions. By analyzing and comparing previous and new data, organizations can understand what happened in between. Then, organizations can come up with metrics and action plans to drive their performance. It involves boosting customer loyalty, increasing sales, improving and retaining successful practices, and enhancing employee productivity.
According to a PwC poll of 1,000 corporate executives, data-driven firms were three times more likely to achieve big gains in their decision-making capabilities.
A data-first approach is required for a digital-first enterprise strategy. In a multi-cloud context, a well-planned data strategy for a digital company gives “business transformation opportunities, cost reduction, better engagement, and maximum flexibility.”
To get the most out of data, organizations must create an effective data analysis process. This procedure entails objective setting, data collection, cleaning and analyzing data, and data visualization.
Before collecting data, defining the goals of the organization is important. Businesses can choose the type of data to collect and evaluate it to ensure it is aligned with their goals. Then, businesses must integrate data using tools such as Informatica PowerCenter, SQL Server Integration Services (SSIS) by Microsoft, AWS Glue by Amazon Web Services (AWS), and Alteryx Designer..
All data must be gathered in one place to be examined. Companies must clean their data by removing irrelevant and unwanted information, fixing structural errors, and filling out the missing data in order to produce accurate findings. To better understand the data, organizations should use data analysis software and other technologies.
Some data analysis software available are XLSTAT, the leading data analysis and statistical solution for Microsoft Excel; Python, a powerful tool consisting of materials for any aspect of scientific computing; and SAS, a statistical software for business intelligence and data management.
To acquire useful insights, businesses should dive deep into the data. They should analyze and narrow down the results of the gathered data to draw conclusions. Then, organizations must interpret the results to figure out the best next steps to reach the goals established in the beginning of the process.
Organizations should deliver information in a readable and understandable format. Businesses can present data using graphs, maps, and charts. Data visualization can help companies compare data sets and observe their relationships.
Data analysis helps anticipate future trends more precisely, allowing organizations to determine where they are headed and what they need to get there.
To learn more about data analysis, explore The KPI Institute’s reports and free webinars and stay tuned for the next schedule of the Certified Data Analysis Live Online Course.