Data: The language of success

In the simplest terms, data are such characteristics or pieces of information that are collected through observation or survey. Professionals from every industry need data to make decisions. Data, in the form of numerical information, percentages – show the behavior of consumers and trends of various processes. Such information is used as primary research by researchers and as a foundation to extract more precise data.
Data has been changing our world as we speak. The advent of the Internet and digital media in particular led to the human’s ability to record, read, and understand data. The many Android and iOS applications that we use on our smartphones record data in real-time. Companies and researchers know how many people from a geographical location are using a ride-hailing taxi service, ordering food, using Google Maps for navigation, ordering products online, or visiting a specific page of a website.
This information takes various forms and styles across the Internet spectrum. Digital media advertising agencies can see how many visitors have clicked to their advertisements placed on various websites. Social media works entirely on data. Its new products rely on the data received from visitor’s behavior and the kind of content they share. In this regard, two types of data are of importance. They are: human-readable data, also call as unstructured data, and machine-readable data or structured data.
Human-readable refers to information that only humans can study. This includes images, videos, and text. On the other hand, machine-readable data refers to information that is accessed and comprehended by computer programs. Examples of machine-readable data include IP addresses, SSL encrypted HTTP messages, image files viewed by image viewers, database information, bar codes, QR codes, magnetic stripes, near field communication technologies, wireless communication, etc.
While humans have developed such applications and technology to gather data, the real task is to have it implemented into meaningful information. This information in the form of easy-to-understand graphs, charts, and illustrations helps industry professionals in many ways. They can identify opportunities and strengths, shortcomings and weaknesses, doubts, and threats. For instance, doctors can use data to see what types of illnesses are prevalent in a certain population. Automobile corporations can determine what kind of vehicles are being used by individuals and corporations. Digital marketers can gauge the kind of products people are ordering online. Bankers can see what type of bank accounts people are opening. Publishing houses can observe what genre of books people are interested in reading. The list goes on.
Data, in the broader context, lets organizations improve their product and service based on the user’s feedback. It also facilitates companies pinpoint a problem and resolve it before it becomes too big to handle. Companies also use data to observe the historical analysis of their past actions. Based on such information, they can take the best action. Data also reduces the guessing games that companies take when implementing a decision. With data on their side, they are well-informed about the tasks they need to complete and are also aware of the kind of results they will get.
For instance, The New York Stock Exchange generates about one terabyte of new trade data per day. Stock market analysts and key stakeholders can use such data to find out what stocks to invest, which stocks to ignore, and what kind of earnings they will generate. Netflix also uses data to recognize the viewers’ trend. The data shows what kind of programs are the most watched, which ones are the most downloaded, and which series or films are creating the most conversations on various platforms over social media.
Businesses as small as grocery shops operating at one location can use data for their advantage. They can classify what products are the most purchased and which products do not need advertising to be sold. All companies from every sector and industry must have a department that works with data. They should have a viable mechanism to record data along with a skilled team to analyze, interpret, and streamline the data to present meaningful information. Special emphasis must be given to sharing this information with the general public. It will lead to the growth of the industry. Furthermore, business schools and universities must offer undergraduate and postgraduate courses in data science. This field of study is the future as data is affecting our lifestyle more than ever.

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