What matters with Big Data is what organizations do with data. Big Data can be analyzed to get ideas that lead to better decisions and strategic business movements.
When we talk about Big Data, we mean data sets or combinations of data sets whose size (volume), complexity (variability) and speed of growth (speed) hinder their capture, management, processing or analysis using conventional technologies and tools, such as relational databases and conventional statistics or visualization packages, within the time necessary for them to be useful.
The complex nature of Big Data is mainly due to the unstructured nature of much of the data generated by modern technologies, such as web logs, radio frequency identification (RFID), sensors built into devices, machinery, vehicles , Internet searches, social networks like Twitter, laptops, smartphones and other mobile phones, GPS devices and call center records.
In most cases, in order to effectively use Big Data, it must be combined with structured data (usually from a relational database) of a more conventional commercial application, such as an ERP or a CRM.
Why is Big Data so important?
What makes Big Data so useful for many companies is the fact that it provides answers to many questions that companies didn't even know they had. In other words, it provides a reference point. With such a large amount of information, the data can be molded or tested in any way that the company deems appropriate. In doing so, organizations are able to identify problems in a more understandable way.
The collection of large amounts of data and the search for trends within the data allow companies to move much more quickly, smoothly and efficiently. It also allows them to eliminate problem areas before problems end their benefits or reputation.
Big Data analysis helps organizations take advantage of their data and use it to identify new opportunities. That, in turn, leads to smarter business movements, more efficient operations, higher profits and happier customers. The most successful companies with Big Data achieve value in the following ways:
- Cost reduction. Large data technologies, and cloud-based analysis, provide significant cost advantages when it comes to storing large amounts of data, in addition to identifying more efficient ways of doing business.
- Faster, better decision making. With speed and analytics in memory, combined with the ability to analyze new data sources, companies can analyze information immediately and make decisions based on what they have learned.
- New products and services. With the ability to measure customer needs and satisfaction through analysis comes the power to give customers what they want. With Big Data analytics, more companies are creating new products to meet customer needs.
For example:
- Tourism: Keeping customers happy is key to the tourism industry, but customer satisfaction can be difficult to measure, especially in a timely manner. Resorts and casinos, for example, have only a small chance to turn around a bad customer experience. Big data analysis offers these companies the ability to collect customer data, apply analysis and immediately identify potential problems before it is too late.
- Health care: Big Data appears in large quantities in the healthcare industry. Patient records, health plans, insurance information and other types of information can be difficult to handle, but they are full of key information once the analytics are applied. That is why data analysis technology is so important for health care. By analyzing large amounts of information - both structured and unstructured - quickly, diagnoses or treatment options can be provided almost immediately.
- Administration: The administration is facing a great challenge: maintaining quality and productivity with tight budgets. This is particularly problematic with regard to justice. Technology streamlines operations while giving management a more holistic view of the activity.
- Retail: Customer service has evolved in recent years, as smarter shoppers expect retailers to understand exactly what they need, when they need it. Big Data helps retailers meet those demands. Armed with endless amounts of customer loyalty program data, shopping habits and other sources, retailers not only have a deep understanding of their customers, but can also predict trends, recommend new products and increase profitability.
- Manufacturing companies: These display sensors in their products to receive telemetry data. Sometimes this is used to offer communications, security and navigation services. This telemetry also reveals usage patterns, failure rates and other product improvement opportunities that can reduce development and assembly costs.
- Advertising: The proliferation of smartphones and other GPS devices offers advertisers the opportunity to target consumers when they are near a store, cafeteria or restaurant. This opens up new revenue for service providers and offers many companies the opportunity to get new prospects.
