How to measure and determine the value of big data

20 January 2020by admin

Big data refers to extremely large and complex datasets that traditional data processing methods are not able to handle efficiently. These datasets typically include a wide variety of data types, such as structured data (i.e. data in a tabular format), unstructured data (i.e. text, images, and videos), and semi-structured data (i.e. data that has some structure but not as much as fully structured data). The data is often generated at a high velocity, volume, and variety, making it difficult to store, process, and analyze using traditional data processing technologies.

Examples of big data include social media data, sensor data from the Internet of Things (IoT), e-commerce data, and financial market data. Businesses, governments, and researchers are using big data to improve decision-making, identify new business opportunities, and gain insights into customer behavior. The technologies and tools used to handle big data are commonly referred to as big data technologies and include Apache Hadoop, Apache Spark, and NoSQL databases.

Big Data has become a popular topic in the business world, and it’s important for companies to understand how to measure and determine its value for their business. The value of data is subjective, and what is valuable for one business or user may not be for another. There are two primary outputs when it comes to the value of data: its ability to generate cash flow and its ability to solve problems. To extract the highest amount of benefits from big data, companies should focus on the following five aspects:

  1. Transparency: Analyzing data within an organization can identify inefficiencies and lead to increased transparency between departments, which can improve employee satisfaction.
  2. Discovery: Analyzing transactional data can provide new insights and patterns that may have not been identified before.
  3. Customization: Analyzing big data can lead to creating different customer profiles and customizing products to fit specific market segments, which can increase value for customers.
  4. Automation: Algorithms that analyze big data can replace manual decision-making and optimize processes, reducing costs and increasing productivity.
  5. Innovation: Analyzing data related to user behavior can identify the need for new products or upgrades, which can generate more sales.

In addition to these five aspects, there are six metrics that can affect the value of data: time, legality, context, quality, diversity, and volume.