Today, many companies are using data analytics to make the most of available information and improve their business strategies. Show
When talking about data analytics, the term big data is often used, referring to the collection, management, and analysis of a large volume of data that, due to its size and complexity, exceeds the processing capabilities of traditional tools. Data analytics, if used properly, provides a competitive advantage over other companies in the industry by
enabling organizations to identify new opportunities and leverage their insights to make strategic decisions. Despite the complexity that can be attributed to them, any company can take advantage of their benefits with the right methodology. In this article, we share some tips on how to apply data analytics in business decision-making. What is data analytics?Data analysis (DA) consists of inspecting a series of data to detect trends and draw conclusions about the available information. This is done through specialized software that transforms the information into powerful visualization tools to maximize strategic decision-making. The goal of data analytics is to drive business performance. Decision-making based on data analyticsTo make decisions based on data analytics, it is necessary to ensure that the available information is well organized, accurate, and easily interpretable. The first step is to create a standard procedure for integrating data across different sources from both inside and outside the organization. After automating this first phase, it is time to monitor and analyze the values obtained from it. This is done through interactive dashboards specifically designed to make data analysis visual and intuitive, providing the possibility of understanding the information in a clear and fast way. In addition, this system extracts data in real-time, allowing for more accurate analysis. The use of data to guide decision-making in business strategy is known as "data-driven decision making". Let's take a look at some stages of this methodologyDefining the ProblemFirst, it is necessary to know the initial state of the situation and, if there is a problem, to identify it clearly. To do this, questions such as: What is the ideal scenario of this analysis? What is the current problem? Data preparationOnce the problem is identified, it is necessary to understand what data needs to be analyzed to improve the baseline situation or solve the problem. In this case, some questions that might help are: what data needs to be collected to solve this problem? How can such data be obtained? Data processingOnce the necessary data have been obtained, the next step is to process them and prepare them for further analysis. In this phase it is important to question which information is relevant and which should be suppressed, that is to say, to carry out a cleansing of all the data to obtain the information that is really useful for our purpose. Data analytics to generate knowledgeFinally, we move on to the data analysis stage, to investigate the problem and find possible solutions. In this phase, we must answer what information about the problem the data provide us with and how this knowledge helps us to solve the problem. ImplementationIt is time to implement the analysis performed and the decisions made based on the data obtained. Data archivingFinally, the last stage consists of the electronic archiving of all this useful information resulting from data processing and analysis. Either for use at the same time or at a later time, keeping them under data protection legislation. Conclusion: data analytics is key to making good decisionsThe high level of competition in the market forces large businesses to resort to data analytics to improve their decision-making capacity. Today, a large amount of information is stored, allowing the use of artificial intelligence for the generation of reports and dashboards that facilitate the search for solutions, which ultimately aim to optimize the profitability of the business. Through data analytics techniques, it is possible to interpret raw information to detect trends or discover revelations that will help in decision making to achieve business success. A recent study found that we create almost 2.5 quintillion bytes of data each day. Enterprises today have access to different kinds of data collected from various customer touchpoints, including websites, business apps, social
media pages, mobile devices, blogs, documents, archives, and more. However, just gathering data isn’t enough to create a positive impact on your business. You need to analyze and transform the collated data into pieces of value-added information. Want to begin your career as a Big Data Engineer? Check out the Big Data Engineer Training Course and get certified. Let’s look at these three ways in which organizations are using Big Data to drive critical business decisions and enhance their business performance and ROI: 1. Real-time Data to Improve Customer Engagement and RetentionCustomer service is one of the most vital areas on which organizations must deliver metrics today. Companies have been using real-time data to offer one-on-one personalized services and solutions to its customers. Kroger uses Big Data to provide customized loyalty programs to its customers. The company utilizes the data collected from about 770 million consumers to generate actionable insights that help the brand in enhancing its customer loyalty and profitability. Kroger claims that 95 percent of its sales are rung up on loyalty cards and has reported 60 percent redemption rates and over $12 billion in incremental revenue. This has helped the company stay profitable even during the global recession. 2. Enhance Operational EfficiencyToday, companies are leveraging data to automate processes, optimize selling strategies, and enhance the overall efficiency of their businesses. For example, Tesla’s vehicles are embedded with sensors that collect data and send it to the central servers for analysis. This helps the company improve the performance of their cars. The company also informs individual vehicle owners about priority repair or servicing. Another useful application of Big Data is Tesla’s autopilot software. Today, Tesla logs more miles per day than the total miles logged by the Google driverless car program since 2009. It has also generated roadmaps for driverless cars by compiling all this data into the cloud. These roadmaps are considered to be 100 times more accurate than standard navigation systems. The enhanced autopilot software helps match a car’s speed to traffic, guide lane changes, and self-parking without the driver’s intervention. Can you imagine an increase in customer base, without extra resource allocation? Sprint, a telecommunications company, uses Big Data analytics to reduce network errors, optimize resources, and improve customer experience by analyzing real-time data. This has helped the brand achieve a 90 percent increase in its delivery rate. Why Should Professionals Prepare For a Career in Big Data?Nearly every industry today is improved with the implementation of Big Data, and similarly, every career field is significantly enhanced when the ability to collect and analyze Big Data is added to the mix. Getting trained in Big Data Analytics will help you broaden your professional horizon. Here’s how:
Preparing yourself with Big Data skills will help you stay relevant and contribute towards the growth of your organization, no matter what industry that may be in today. ConclusionAs more organizations move towards a data-based decision-making approach, it is essential that enterprises foster learning and invest in their employees to gain value-added certifications in this domain. Companies must take initiatives in sponsoring employees for relevant training programs on analytical tools and techniques that will arm their teams with the knowledge and skills required to leverage data for informed decision-making. Simplilearn's Big Data Hadoop training course and Data Engineer Certification Program would be a suitable course that would How does data analysis help with decision making?Through data analytics techniques, it is possible to interpret raw information to detect trends or discover revelations that will help in decision making to achieve business success.
What are the advantages of using data to make decisions?5 Benefits of Data-Driven Decision Making. Increased accountability.. Better efficiency.. Alignment on company-wide goals.. A sense of ownership at every level.. Transparency.. How can dataData-driven decision-making (DDDM) is the process of using data or facts to inform decisions rather than just relying on intuition, observation or guesswork. On a daily basis, multitudes of business decisions are made across an organization—from the executive boardroom down to the frontlines with customers.
|
