In this digital age, it’s become more and more crucial for a business to be data-driven, but what does that exactly mean?
These days, it’s common practice for many companies to collect data. More often than not, however, they don’t know how to harness their potential. According to recent research, up to 55% of collected data by companies is left unanalyzed. That’s certainly unfortunate, considering the powerful insights you can glean from the analysis of such data.
Once businesses learn how to make use of data, they can be more confident in making decisions as they are assured of getting successful results since they’re basing their actions on actual data.
But what is business data analysis, and why is it important for companies?
Defining Data Analysis
Simply put, it is the process of collecting data for the purpose of organizing & analyzing it so one can draw helpful conclusions from it. Both logical and analytical reasoning is used to get information and insights from the data, which companies can then use to make informed decisions.
Data analytics is applied in many fields, such as market & product research, customer reviews, positioning, sentiment analysis, and any other fields in which data exists.
Examples of Data Analytics
If you’re not already familiar with the abstract idea of data analytics, you might find it hard to grasp its concept. Here then are some common examples that can further illustrate what it’s about.
- Descriptive Analysis – This type reviews past data and then simply describes what happened. This is used when a company wants to track revenue, Key Performance Indicators (KPIs), sales leads, and more.
- Diagnostic Analysis – This aims to figure out the cause or reason behind what happened and is usually the next step after descriptive analysis. This kind of analysis comes in handy when businesses want to figure out which marketing efforts were most effective in increasing sales leads.
- Predictive Analysis – This type predicts what is going to happen in the future. It identifies trends based on past data and then uses those to create forecasts relevant to the business and the industry. It can be applied to issues such as qualifying leads, sales forecasting, and risk assessment.
- Prescriptive Analysis – This is the most complex type from among the four examples as it combines the information gathered from the previous three types and uses them to create a decisive plan of action. This is the level in which businesses make data-driven choices that can affect the future of their organizations.
Why Data Analysis Matters
Ultimately, data analytics is more than just presenting numbers and figures. It involves a thorough & detailed approach to recording, organizing, analyzing, and presenting data in a clear & concise manner so that business owners & executives can make informed decisions for their organizations on important issues such as customer trends, behavior predictions, increasing profitability, and more.
Once you adopt data analysis techniques in your business, you’ll be better equipped to identify the causes behind particular events and understand your company’s objectives and future direction. Most of all, you will gain technical & practical insights about how your business works.