Big Data is a huge trend in the business world. Many businesses are now turning to “Big Data” to gain lucrative insights, identify emerging trends, predict shifts in consumer and market behavior, and ignite innovation. But what exactly is behind the term “Big Data“? What are the advantages of using them and what direct application scenarios are there? You can find the solutions in our following blog post.
In the current, digitized business world, data is produced, processed and stored at all times of the day and night, be it on internal data carriers, in the cloud or in edge computing at the “edge” of a network. At the same time, the current competitive landscape is in constant flux. As a result, companies must be in a position to be able to react quickly and flexibly to changes – otherwise they run the risk of being overtaken by the competition.
Big Data: Definition & Explanation: What Is Big Data?
In the broadest sense, the word “Big Data” describes unstructured, semi-structured and structured data collections that are generated, stored, analysed and used in large quantities, in enormous diversity and with even greater speed. Furthermore, the neologism is now also used as a term for a large number of new concepts, technologies, IT systems and methods with which companies can advantageously analyse, process and make use of the increasing flood of data.
Just as with conventional data analysis, the goal behind the “Big Data” concept is to filter out profitable information from various data and to use it for the success of entrepreneurial plans. But in contrast to conventional data processing, “Big Data” is characterized by various key characteristics that require and influence one another.
These include:
- V for Volume: Volume refers to the amount of data available and is the basis of Big Data. Normally one speaks of “Big Data” when the volume of data in a defined, definable amount of data reaches the size of terabytes, petabytes, exabytes and beyond.
- V for Velocity: Velocity refers to the speed of data generation and data processing. This is a crucial factor for companies that need fast data streams to make the most optimal business decisions.
- V for Variety: Variety refers to the variety of data types, such as photos, videos or sensor data. The data can come from both internal and external sources of a company and can be unstructured, semi-structured or structured at the same time.
- V for Value: Value refers to the economic value of big data to an operation, which can be gained through appropriate analysis. The value can vary depending on the industry. In this way, “big data” can be used, for example, to optimize production processes, open up new target groups or create completely new products.
- V for Veracity or Validity: Veracity or Validity takes into account the correctness, truthfulness, reliability, meaningfulness and trustworthiness of the data. Since these come from different sources, a successful analysis of mass data depends on the nature of the existing data and the method used to process and analyze data.
- V as in Viability: Viability describes the relevance and usability of the collected data in order to produce a benefit from them.
- V for Visibility: Visibility takes into account the visualization of data. If companies succeed in making all data present and usable with the right big data technology, new business values can be generated or new business models can be developed.
- V for Volatility: Volatility describes the storage and deletion of data. For example, data for real-time processing does not necessarily have to be stored after this processing. Customer data, on the other hand, usually has to be kept permanently. In addition to the available storage space, legal or company-internal conditions play a role.
- V for Vulnerability: Vulnerability describes the vulnerability and in particular the data security of “Big Data”.
What Application Scenarios Are There?
As an essential resource, big data helps companies to make business-critical decisions and to secure significant competitive advantages. It is therefore used in a wide variety of business scenarios:
- Economy: By evaluating mass data, companies can gain important and fundamental insights into the market, their customers or their competitors and in this way, among other things, provide individual offers, optimize the experience of customer interactions, minimize client migration or proactively deal with problems.
- Industry: In industry, the targeted evaluation and use of your own machine data can increase the efficiency of production and enable companies to work more sustainably.
- Product Development: Even in product development, more and more big data is being used to predict customer demand, plan, produce and launch new items.
- Marketing: Another tried-and-tested field of application for “Big Data” is marketing. However, this is less about the data per se and more about the results that can be drawn from Big Data. On their basis, the appropriate marketing measures can be taken and implemented.
- IT security, risk prevention and compliance: Big data also plays a decisive role when it comes to IT security, risk prevention and compliance. Because the IT threat landscape and compliance requirements are constantly evolving, companies can use the right big data technology to identify possible discrepancies, unwanted or incorrect transactions at an early stage.
What Are The Advantages Of Using Big Data?
Since companies can already gain decisive insights by examining and evaluating a small amount of structured data, the targeted use of “Big Data” brings unprecedented opportunities. With the help of “Big Data”, companies can, among other things
- create a secure basis for decision-making and make better decisions
- Finding and improving potential for improvement in business processes
- develop new products, services and optimized offers
- Make product development activities, marketing activities or sales activities more efficient
- increase profitability
- Make prices dynamic
- optimize customer contact
- exploit the market potential
- identify the factors behind malfunctions, problems, defects or even fraudulent behavior before it
- affects the company
- reduce operating costs
Conclusion
The fact is: The global volume of data will continue to increase in view of increasing digitization and networking – and with it the importance and relevance of “Big Data“.
Consequently, every company should deal with the topic at an early stage and bring together the necessary big data skills. Only in this way can “Big Data” actually form into a significant entrepreneurial success factor.
Also Read: Metadata And Its Importance In Company Security