Analyzing data plays a major role in a success of any business. For people who do not know, data analysis is the decoding of the data which has been collected or organized in the form of a table, chart, graph, or any other representation. In today’s date and time where competition is at its peak, any business can face a huge loss if they stop meeting consumer’s requirements. Businesses can simply lose their profit to someone who does it better. The very simple solution is to keep up with the consumer’s changing requirements. This is when data analysis comes into play.
With regular data collection and analyzing of that data, business owners can track their sales, study customer feedback and apply this knowledge in their business’s strategy. This not only attracts customers but increases a company’s revenue massively. Many of the top influential business owners actually use Devo which helps them make business-critical decisions and analyze all their machine data. Business owners need a quick access to their data all the time, so with Devo, one can get high speed and uniform access to all their data regardless of its age and sources. Analyzing data has become so important that it could make or break the existence of the company. Analyzing of data can mean a difference between an ordinary business & a leading business.
The Role of Raw Data
Every card transaction which is made, any app working on your smartphone and every click of the mouse contributes to an increasingly large set of the database. Raw data represents the individual records of the company which are processed every day. A company cannot learn much from each individual data. Individual data can only provide information much later after it has been processed to provide any relevancy or context. It is after the analyzing of data, it reveals patterns such as best selling days, lowest selling items or even customer’s feedback. In today’s time, companies need to process and report on large volumes of data. Cindi Howson, President of ASK suggested that on average, a manager spends 2 hours per day hunting for data.
Every business needs to find well-organized methods to turn their data into useful information. In today’s competitive market, it is difficult for the managers to study high volumes of data and make the rightful decision. Making decisions as per the data is becoming extremely complex as business competes in the global market. Business need tools to analyze data to make better decisions.
People usually start with a question and then look forward to data analyzing to find the answer. In a medical/pharmacy company, questions might include, “which are the most selling medicines?” and “what are the collective sales in last month?” But what if you do not have a question, to begin with? To explore data without a defining question is called “data mining”, It can sometimes reveal interesting and engaging patterns in the data that are worth exploring. It is important that you are open to unexpected patterns & explanations whenever you analyze data. Sometimes the most interesting stories to be told with data are not the ones you set out to tell.
How Is Data Analysis Performed?
As mentioned above, Data analysis is the process of decoding of data with the goal of discovering useful information. This includes one or more of the following process
- To Define Objectives: Any study must begin with a set of clearly defined objectives. Decisions made in this process directly depends on how clearly the objectives of the study are defined.
- To Pose Question: An effort is made to ask a question in the problem domain. For example, do bikes get into accidents more often than cars?
- Collection of Data: Data which is relevant to the question must be gathered from various sources. In the above example, data may be gathered from different sources which may include hospital details, DMV, insurance claims or accident reports. The raw data is collected in many different formats. The data collected must be cleaned & converted so the tool can analyze the data efficiently.
- Data Analyzing: This is the step where the tool imports the cleaned and aggregated data and puts it into use. These tools allow the person to explore different patterns and charts and answer the what if questions. The data is decoded and organized in the form of a table, chart, graph, or any other representation. The user can also draw conclusions and predictions by analyzing data and summarize them in a report.