BIG DATA PROJECTS

Better Decision Making:

Big data facilitates the decision-making process by providing business intelligence and advanced analytical insights. Data-driven insights enable the business to create more customised products and services, well-informed campaigns and strategies for the betterment of the organisation.

Reduce Costs Of Business Processes:

The businesses have integrated automated processes to enhance their performance. As companies collect more data on their customers and the complexities of their supply chain, reach an unprecedented level beyond the traditional Enterprise Resource Plan(ERP) systems. As a result, a new market for big data connecting ERP systems has emerged. This allows a large volume of data to be analyzed and automated in their systems. Thus reducing operational costs greatly.

Fraud Detection:

Big data analysts use machine learning algorithms and artificial intelligence to detect anomalies and transactions. Big data projects are important for credit card companies to identify account information, material or product access. And also can serve its customers by early identification of frauds before something goes wrong.

Increased Productivity:

Utilising big data to expedite and improve the daily procedures of the business, measure performance and give more accurate readings on productivity. Big data also help productivity on a more individual level and can give different insights into how productive an employee will be.so big data not only benefit businesses but also benefits the employee's productivity individually by tracking their progress digitally.

Improved Customer Service:

Big data analytics provide more information to businesses, that can be utilized to create more target marketing schemes. It also helps companies to know about their customer's experience with their products and services. Thus helpful in offering a better service that can improve customer satisfaction, enhance relationships and build loyalty.

Increased Agility:

Big data helps companies to improve their business tactics and strategies which are very helpful in aligning their business. Big data projects analyse huge data sets related to customers and enable companies to gain insights ahead of their competitors by addressing the pain points of customers more efficiently and effectively.

Questionable Data Quality:

The Quality of the data sets and resulting analysis must be good for Data-driven decisions and Operational strategies. There is a risk that the insights found from the analytics of such data might be worthless or may be harmful.

Transferability:

Since the data analysed lies behind a private cloud or a firewall, it takes a technical risk to efficiently get this data. Further, it may be difficult to consistently transfer data to specialists for repeat analysis.

Cost and Infrastructure Issues:

Being big data in constant evolution and with the objective of processing larger and larger volumes of information, the cost of its implementation is so high that only large companies can afford the investment in the advancement of their big data techniques.

Complexity:

The information collected from consumers and other organizations must navigate which increases the complexity. Therefore strict data privacy rules and regulatory compliance demands. Since big data volume increases, the storage, transmission, and data governance tasks become difficult to manage.

Security Risk:

Data Privacy is a great challenge in this digital world. It aims to safeguard personal and sensitive information from cyberattacks, security breaches and intentional or unintentional data losses. Big data analysis violates privacy principles.