You have learned how Big Data is defined and what options there are for using the large amounts of data. In this chapter, we will go into more detail and deal with the analysis of Big Data. This specialist field is known as BigDataAnalytics.
Big Data Analytics − Theory
The first step is to collect largeamountsofdata from different sources, which have different formats. This is often done using search queries. Then the data is prepared for further processing. One problem is often that large amounts of data are available in an unstructured form and in completely different formats and therefore cannot be captured by conventional database software.
Big Data Analytics therefore uses complicatedprocesses to extract and capture the data. The data is then analysed using special Big Data software. Finally, the results are processed and presented.
It is important that the software used is capable of quickly implementing many search requests and quickly importing and processing the various data records. In order to be even more powerful, many systems do not use the harddrivespace (like conventional database applications) for data processing, but rather the usually much faster mainmemory. This way, the access speed can be increased, and analyses can be performed almost in real time.
Remember
The analysis of Big Data can be roughly divided into three different areas:
Procurement of data from many and various sources by using search queries
Evaluation and optimisation of the collected data
Data analysis and the summary and presentation of results
A powerful and suitablesoftware is very important for that.
Big Data Analytics – In practice
It is interesting to note that Big Data Analytics is still in its infancy in most companies and the opportunities offered are farfrombeingexhausted. On average, companies analyse only a little more than a third of the data generated by digital contact with their customers (e.g. via online shops or websites).
The reason for this is often the strict data protection regulations which make Big Data Analytics more difficult. The laws and regulations that govern data protection are discussed in more detail in the following chapter. In reality, however, in many respects companies are not yet ready to effectively use the large amounts of data for themselves. The following areas play an important role:
First of all, it is advisable to distribute the results correctly: the data sources should come from different areas, the results should be used in several areas of the company. A suitable strategy is also required: a company should know for what purpose the large amounts of data are being analysed. A suitable corporateculture is also very important, new technologies, for example, should not be rejected in principle, but rather considered realistically.
Most companies do not have their own department for data analysis. Nevertheless, some employees should bring the necessaryexpertise with them or acquire it in training courses. New employees may need to be hired. Responsibilities and authorisations must also be defined within the company.
Efficienttechnology, in the form of suitable Big Data analysistools, is required for the analysis. However, which tools are suitable depends on the previously defined strategy or the defined purpose of the analysis. Last but not least, a suitable data protection strategy is also essential to ensure that personal data of individuals is not disclosed to the public. A dedicated data protection expert within the company ensures that the analysis of the data complies with the applicable laws and regulations.
Remember
In summary, the following points are important for Big Data Analytics to succeed in a company:
a Big Data strategy – defining the purpose of the analysis
a suitable corporate culture – openness to new technologies
personnel with the necessary know-how – training or recruiting
a powerful technology – appropriate big-data analysis tools
an appropriate data protection policy – compliance with applicable laws and regulations
You have learned how Big Data is defined and what options there are for using the large amounts of data. In this chapter, we will go into more detail and deal with the analysis of Big Data. This specialist field is known as Big Data Analytics.
Big Data Analytics − Theory
The first step is to collect large amounts of data from different sources, which have different formats. This is often done using search queries. Then the data is prepared for further processing. One problem is often that large amounts of data are available in an unstructured form and in completely different formats and therefore cannot be captured by conventional database software.
Big Data Analytics therefore uses complicated processes to extract and capture the data. The data is then analysed using special Big Data software. Finally, the results are processed and presented.
It is important that the software used is capable of quickly implementing many search requests and quickly importing and processing the various data records. In order to be even more powerful, many systems do not use the hard drive space (like conventional database applications) for data processing, but rather the usually much faster main memory. This way, the access speed can be increased, and analyses can be performed almost in real time.
Remember
The analysis of Big Data can be roughly divided into three different areas:
A powerful and suitable software is very important for that.
Big Data Analytics – In practice
The reason for this is often the strict data protection regulations which make Big Data Analytics more difficult. The laws and regulations that govern data protection are discussed in more detail in the following chapter. In reality, however, in many respects companies are not yet ready to effectively use the large amounts of data for themselves. The following areas play an important role:
First of all, it is advisable to distribute the results correctly: the data sources should come from different areas, the results should be used in several areas of the company. A suitable strategy is also required: a company should know for what purpose the large amounts of data are being analysed. A suitable corporate culture is also very important, new technologies, for example, should not be rejected in principle, but rather considered realistically.
Most companies do not have their own department for data analysis. Nevertheless, some employees should bring the necessary expertise with them or acquire it in training courses. New employees may need to be hired. Responsibilities and authorisations must also be defined within the company.
Efficient technology, in the form of suitable Big Data analysis tools, is required for the analysis. However, which tools are suitable depends on the previously defined strategy or the defined purpose of the analysis. Last but not least, a suitable data protection strategy is also essential to ensure that personal data of individuals is not disclosed to the public. A dedicated data protection expert within the company ensures that the analysis of the data complies with the applicable laws and regulations.
Remember
In summary, the following points are important for Big Data Analytics to succeed in a company:
an appropriate data protection policy – compliance with applicable laws and regulations
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