Big Data and Data Governance – Importance and Benefits

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Data is undoubtedly the most valuable asset for businesses in the present world. Doesn’t matter what industry we are talking in, Data would surely have a major role in the digitalized version of businesses and act as the medium for their transformation. And as the term ‘Big Data’ is becoming more common day by day in the tech as well as the industrial world, businesses are starting to realize the value of the stored data for their growth.
The digital market is flooded with big and small businesses dealing exactly in the field of Data Analytics and so far, there has been a major disruption caused due to the presence of Bid Data analytics in every market. Market Leaders from every industry have stepped into the field and emerged into the domain of Data Science and Data Analytics just for securing the fate of their businesses in the upcoming digital future. Let us talk about the major trends of data analytics such as Big Data, Data Governance, and Data Lake.

Big Data & Its Importance

Big Data is a complete field of technology dealing with large and complex data sets made up of structured as well as unstructured data. Big data technology deals with the infrastructure, technologies, and tools mainly developed for the management of a large amount of data and information. When talking about the range of Big Data, it is almost impossible to think about processing such huge amounts. So, the development of platforms dealing with a set of technologies to analyze and process enormous amounts of data including structured and unstructured information is the main part of Big Data technology. Big Data technology mainly deals with 5 crucial characteristics of data processing. Big Data works on the following focus points:

• Value: It provides management of various types of information having varied complexities to make it easier for intelligent systems to work on, therefore providing value to the system.
• Veracity: Big Data focuses on the reliability of the information to provide the systems only with significant data, nothing less.
• Variety: Big Data arrays contain heterogeneous formats of information having the ability to be structured partially.
• Volume: As its name suggests, Big Data deals with huge amounts of data daily measured by its physical size, ranging from GB’s to TB’s.
• Velocity: Big Data technology also requires regular updates for real-time processing, therefore, demanding fast transfer of data.

When integrated with other technologies, Big Data has a lot of advantages as it helps businesses in gaining valuable insights using huge amounts of data for processing and providing concluding on its basis. Using Big Data Analytics Solutions, your business too can excel in modern-day markets.

Data Lake, What is it?

From a technological perspective, Big Data can be referred to as a repository that stores immense amounts of unprocessed data in its original format. When compared to a data warehouse system that stores information in tables, a data lake employs a flat architecture to store data. In a data repository, each element is given its unique identifier marked using metadata tags so, in case of any business query, data can be searched from small, separate collections of particular information, making it easier to analyze and solve a particular problem. The main idea of Data Lake is that in an organization, you can store all data in a single data lake rather than placing it in purposely built data stores. It is beneficial as it removes redundant costs of several processes such as transformation as when data is stored in a lake, it is available to everyone in the organization. Another concept of Data Lake is collecting a huge amount of data and then detecting exceptions, patterns, and trends in it using different technologies such as AI & ML. It is because, in Data Science, the more amount of data you have the better it is, and ultimately is beneficial for your data analytics model. And with Data Lakes, you can access all data using the entire set instead of using sample sets that greatly reduces the number of false positives in the output. As data lake is a new concept and is still under constant development there may be varied applications to it based on the need of an organization. It can be used natively as it has such a huge amount of data contained in it, or it can be used in a hybrid form integrated with other forms of storage such as data warehouses.

Data Governance & Its role 

Data Governance refers to the process of management of different properties of data in an enterprise system such as availability, usability, integrity, and security. In an organization, data governance is based on internal standards and policies resulting in controlled data usage. Effective Data Governance results in assuring the consistency and trustworthiness of data and ensures the correct use of it. It is extremely important because businesses witness changes in privacy regulations very often and therefore, data analytics help them to optimize their operations and help in effective decision-making. The main goal of data governance is to fragment data silos of an organization that is build-up due to the absence of centralized and coordinated data architecture in a business. It aims to integrate the data in those systems by collaborative processes and to ensure the proper use of data to avoid the introduction of data errors and misuse of personal and sensitive information. Besides this, Data Governance also provides more accurate and strong regulatory compliance, improved data quality, and lowered operating costs. In absence of effective Data Governance, organizations face data inconsistencies in different systems. It results in the complication of data integration efforts and creates data integrity issues affecting the accuracy of business intelligence, analytics, and enterprise reporting. Apart from that, data errors in the system cannot be correctly identified and fixed. Poor Data Governance can also cause problems in compliance with regulations and laws for organizations. Ultimately all these Data Science Trends helps in the improvement of decision making by businesses, providing insights based on data provided, yielding competitive advantages, and an increase in revenue and profits.


Read More Artificial Intelligence and It’s Importance for Businesses

Conclusion

For businesses big or small, Data Science helps in defining new ways to yield benefits for companies. Using the power of valued data across different industries Big Data helps in quantifying different processes and results in providing huge advantages in the form of insights of analytics information. It helps businesses in creating ways of using different modern technologies such as AI & ML to create their own set of development factors. Data science is constantly facing an expansion of the services it offers to benefit a variety of businesses. Therefore, with the increase in the use of modern technologies, the world is set to become better day by day.