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How the commercial world is making use of Big Data to improve the business outcomes

Our lives have become data-driven. An incredible amount of data keeps generating every moment from all kinds of sources of human activities in the fields of scientific research and development, in academic institutions as well as businesses, the financial and economic sector, various administrative and government actions, legal activities, health care services, manufacturing, retail and many more industries.

Every activity that individuals, organizations, and businesses undertake generates vast amounts of data that reach the database of the systems used by the respective organizations. The enormous volume of data that runs into quintillion bytes daily and better known as Big Data reaches the databases and needs proper maintenance and management for safe storage, retrieval, and sharing whenever required. Companies like offer database administration services for maintaining databases that are like oceans of information.

The days of Big Data

The rate of data generation has gathered unbelievable pace between 2018 and 2019 due to a remarkable increase in economic activities across the globe. The Covid19 pandemic has fueled the data generation so much that the amount of data generated every moment worldwide has acquired astronomical proportions.

As people stay in quarantine and are working from home in compliance with the health advisories consisting of physical distancing to control the spread of the pandemic, there has been an enormous surge in virtual interactions both at personal and professional levels. The increased virtual activities have spiraled the data generation volume almost overnight, and organizations face the massive task of managing Big Data to put it to good use for advancement in the respective fields.  Once again, it highlights the need for professional database administration services that ensure safe data storage, fast retrieval, and sharing.

Social media platforms have experienced an enormous increase in data generation. They have their task cut out to manage Big data, and use it meaningfully to provide a better user experience has become a huge challenge.

The characteristics of Big Data

Reading so far, you must be eager to know what exactly Big Data means.  You must have noticed that the extremely high volume is one of the hallmarks of Big Data.  But there are some other dimensions of Big Data, like its wide variety and the incredible velocity of data generation, that add to the complexity of the much talked about Big Data. Big Data is a massive asset for organizations that must deploy cost-effective and innovative ways of processing information to gather better insights and make better decisions. Big Data is big but complex too, and it requires a lot of technical expertise to manage and make good use of the most important digital asset.

Types of Big Data with examples

Big Data comes in three forms – structured, unstructured, and semi-structured.

Structured Data – There can be many different formats of storing, processing, and retrieving Big Data, but it constitutes Structured Big Data when using any fixed format for the purpose. Information is stored in a highly organized manner, and its accessibility is easy by using search engine algorithms. The most prominent example is the employee database of any organization, where information is stored in a highly structured manner containing the employee names, designations, departments, salaries, etc. The well-organized data makes retrieval fast and easy.

Unstructured Data – Data is available in various forms as every digital activity that we undertake generates data. Whether to store it in a structured manner is the prerogative of the organizations, depending on how they want to use data. Many data like e-mails are best left in the way it exists and is the most glaring example of unstructured data where information is scattered all over the emails, but users can retrieve it selectively.

Semi-structured data – Semi-structured data is a hybrid of structured and unstructured data. Although such data does not belong to any particular type of database, it contains tags or vital information that makes individual elements within the data essential and suitable for segregation.    The HTML is an example of semi-structured data that does not limit the information you can gather from any document but follows a certain hierarchy.  Although HTML uses code for organizing data, you cannot extract it into a database. Traditional data analytics methods do not help extract meaningful information for gaining insights. The ordering database of individual customers that contains the full name of customers and the order id is an example of semi-structured data.

Why is Big Data so important?

Predictive analysis – You can use Big Data in the way you want to gather valuable insights about any process that you are working upon by slicing and dicing data in the way you want to extract the most useful information for development and progress. Using some tools for handling and analyzing Big Data, you can indulge in predictive analysis. It can tell you in advance the possible outcomes of a business process that helps business owners and managers take more meaningful and prompt decisions to assure the results.

 Enhanced consumer experience – Businesses must constantly improve the user experience to gain more trust and confidence in users about the brand and business. The most perceivable use of Big Data is in customer support as companies use various analytical tools to extract valuable information about user expectations and identify the areas for improvement to ensure a better user experience. The use of Big Data empowers businesses to formulate more effective marketing strategies as they can read the mind of users and understand their expectations.

Actionable insights – Big Data consists of data from gathered from the broadest cross-section of the business activities by assimilating data from various sources at a very high speed that points to actionable insights. However, getting the right tools for analyzing Big Data makes all the difference because focusing only on useful data by filtering out unwanted data is the way to get the most from Big Data.

Companies depend on Big Data to generate more and better sales leads that help them stay ahead in the competition.

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