Big Data Analytics is the science of analyzing huge amounts of data to discover hidden patterns, correlations, market trends, and other useful information. With today’s technology, it’s easy to analyze your data and get significant values from it.
The concept of big data and big data analytics has been around for several years; now that most of the organizations have understood the importance of “data”. They have started capturing all the data that streams into their business so that they can apply analytics and get significant information from it. This significant information can help organizations to uncover insights and trends and could be used for future decisions.
Big data analytics helps organizations to understand the importance of data and the information contained within the data. It helps organizations to harness their data and use those information for future decision-making and other business purposes.
Importance of Data Analytics
Big data analytics involves process of converting large set of structured/unstructured raw data to meaningful information that would be useful for organizational purposes. Harnessing the available data would help organizations uncover hidden patterns, current market trends, and other useful information. Big data analytics comes with 6 major benefits, which includes:
- Smarter and efficient business moves
- Higher profits
- More efficient operations
- Faster and better decision-making
- Cost reduction
- New products and services
Other than these benefits, big data analytics brings 2 new benefits, say speed and efficiency. The ability to operate at a faster pace gives organizations and enterprises a competitive edge.
High-performance big data analytics allows you to do things that you would have never imagined. It helps in getting timely insights that helps in decision-making, provides precise answers for hard-to-solve problems, and uncovers new growth opportunities. Most of all, it helps in utilizing the IT resources more effectively and efficiently than before.
Data analytics plays a significant role in decision-making and thereby helps in enhancing the performance and RoI of the business. Data analytics can influence decision-making in 3 main ways, namely
- Enhances operational efficiency
- Real-time data enhances customer engagement and retention
- Increases capacity without extra investment
Applications of Big Data Analytics in Various Sectors
The following are the list of various organizations that implements data analytics:
- Government
- Manufacturing
- Healthcare
- Education
- Sports
- Information Technology
- Travel and Hospitality
- Retail
Government: Data analytics helps governments and law enforcement agencies to streamline their activities while giving these agencies a more comprehensive view of criminal activities.
Manufacturing: Big data helps in enhancing the supply planning and product quality in manufacturing sector. Offers infrastructure for transparency, which in turn helps manufacturers to unravel uncertainties.
Healthcare: Big data analytics has helped healthcare sector improve by offering personalized medications and prescriptive analytics. It helps healthcare providers to offer potentially lifesaving diagnoses and treatment options.
Sports: Big data can be used in sports to enhance training activities and understanding competitors. It also helps in predicting the winners, and future performance of the players as well.
Retail: Big data analytics helps retailers to offer better services to customers, predict purchase trends and recommend new products; this in turn boosts profitability.
Risks and Challenges in Big Data Analytics
For most of the organizations and enterprises, big data analysis is still a challenge. Big data analysis can be done for both structured and unstructured data formats. Data analytics on structured data is simple and easy when compared to analytics on unstructured data. Handling of unstructured data formats has always been a tough task. Since data format varies widely in unstructured data, it cannot be stored in traditional relational databases. Even if these unstructured data need to be stored in traditional databases, it need a considerable amount of effort during data transformation.
Big data analytics possesses several risks including: stealing of data/ideas/work done by users, price discrimination, no proper protection for user’s identity, and much more. There are certain extreme scenarios where governments gather too much private information about the citizens.
If you are still looking for an option to reduce the complexity of the data in your business, big data analytics can be a good solution for increasing the speed and efficiency of the operations. At times, it can be time-consuming when handling huge amounts of unstructured data, but still it reduces the complexity.
