Under Big Data all data collections are grouped together, which can not be evaluated with conventional data processing techniques. This is not only due to the size of the data, but also to its complexity and constant change. In the broadest sense, the term refers not only to the data itself but also to its analysis.
Great technical effort
In order to be able to process the unimaginably large amounts of data, special data memories are required. It is almost commonplace for companies to store data in pentabyte ranges and process data in multi-digit terabyte ranges. In addition, the amount of data is growing exponentially. Calculations from 2011 have shown, for example, that the amount of data doubles every 2 years, which, in addition to the machine data generation, is of course also due to technical progress. More and more data can be collected and stored.
Most big data technologies are tailored to the respective area of application. The most important ones include Hadoop, Mongo DB, Pentaho and Infobright. They enable the processing of a large number of data sets or the respective data set units as well as the import and export of extremely large amounts of data. The complexity of the data or many queries running in parallel do not pose a problem with such technologies.
Applications for Big Data
The sources for big data are just as diverse as the technologies behind data collection and processing. They come from, for example:
– Social media channels
– technical networks
– sensor data
– geospatial data
– Weather satellites
– medical test series
The areas of application for big data in business, science and technology are correspondingly extensive. They range from medical diagnostics and intelligent energy control to the evaluation of web statistics in order to adapt online advertising measures. The purpose of the data collection also differs depending on the area of application. While profitable developments are to be recognized in economic areas and used to the advantage of the company, the focus of online marketing is on the insight into the interests and characteristics of the potential customer.
Big data – advantages in online marketing
According to eshaoxing, the “big data” offer enormous potential for online marketing. Whether page views, purchases, contents of the shopping cart or postings on Facebook – the variety of data on the Internet enables marketing managers to develop a much more precise picture of the target group, to analyze the wishes and interests of potential customers and to create customized offers for them accordingly.
The better you understand customers and their needs with the help of big data, the easier it is to make predictions about their future behavior or to personalize campaigns. This of course also increases the likelihood that the customer will react positively to the offer, ergo: that he will buy. After all, he is not being suggested anything, but a product / service that fits his current needs.
The data that can be used in online marketing can be collected as follows:
– Online purchases
– Website visits / visitor behavior
– social networks
– Inquiries to search engines
– mobile usage data
They can be used, for example, for:
– customer loyalty
– Website design, e.g. personalization of the website by region
– Cross-selling measures
– more targeted email marketing
– tailor-made management of marketing campaigns
– trend analysis
– more targeted use of company resources
– Service optimization
– Demand and sales analyzes
The successful use of big data in online marketing, however, requires that the data collection is preceded by specific questions. What should be evaluated and why? What is the goal of the data collection / evaluation. Only then is targeted data collection possible, for example with the help of Google Analytics, which in turn is the prerequisite for targeted evaluation and profitable use for the company.
Further information: 10 examples of BigData campaigns that are amazing
Criticism of the collection and use of big data
In addition to great potential, big data also brings with it numerous points of criticism. Because it is not always clear exactly where data is being collected, by whom, and what it is being used for. In many cases, private areas are accessed, often without notifying the user beforehand and obtaining his or her consent. Companies are therefore faced with the challenge of using the economic advantages of big big data on the one hand and complying with data protection on the other.
There is also criticism of the type of data evaluation, as it is a purely technical collection of the data and its evaluation is also purely technical. The quality of the data would not be given sufficient consideration. In addition, a large amount of data does not automatically mean a good data foundation.
In this context, by the way, the advantage of a targeted, purposeful collection of data is again noticeable. This not only saves costs for the IT infrastructure, but also simplifies information on data processing for users.
The data must be stored in accordance with German data protection law. In addition, companies must consider consumer protection when using data and prevent data manipulation.