We read the term big data every day on blogs, newspapers, websites.
But do we really know what big data are and how they can be used by companies?
Our approach to Big Data
In our daily life, we perform countless actions, more or less complex, such as a simple Google search, a purchase in a supermarket, interaction on social networks or a simple website. All this generates an extremely large amount of information, a volume of heterogeneous data, stored and analyzed even in real time. These are called Big Data.
Volume
the amount of heterogeneous data from different sources: database, log, email, social media, events etc ...
Varietà
the heterogeneity of the generated data is important, since in order to have more accurate and deep analyzes, it is necessary to consider both structured and unstructured data.
Velocità
the speed with which the data are generated and transmitted, in real time, in order to carry out the analysis.
Veridicità
Valore
The ability to transform data into value. The fairly obvious concept always concerns the quality of a data item, and it is necessary to define what are the elements that characterize the data item itself. That means to apply parameters, to define the extent to which the data must be taken into consideration.
Analytics
What is analytics? What are the differences with the analysis?
While the analysis focuses on what happened, therefore on the past, the analytics is focused on why it happened and what will happen next.
The analytics tools are divided into 4 categories:
- Descriptive: they aim to describe the past and present situation of the processes;
- Predictive: they analyze the data and try to make future predictions;
- Prescriptive: they propose possible solutions and choices based on the analyzes they carry out;
- Automated: they autonomously make choices based on the analyzes carried out.
Real time analytics
Real time analytics is the approach that allows the analysis of data in real time, using data streaming processing, in this way choices can be made faster, and have the current situation under control.Machine learning e augmented analytics
Machine learning and augmented analytics is an approach used for those who want to do the analysis themselves, because this process automates the identification of data sets, patterns and hypotheses, offering more in-depth analysis.
Self service data analytics
Self service data analytics is the spread of tools that allow the user to independently manage the data query process. These tools offer different solutions to the user including:
- Reports: these are analytical documents carried out in summary form prepared by Data Scientist and Data Analyst;
- Periodic dashboards: they are dynamic dashboards, in which the user reacts with the data, but in a limited way, by analyzing periodically processed data, therefore not updated at the time when the data source is updated;
- Real-time dashboards: they are dashboards updated in real time, and therefore show a real situation at the time of consultation;
- Visual Data Discovery tools: they are tools that allow the development of complex analyzes, such as forecasting or optimization analyzes.
Where to use these technologies?
Marketing
The sector in which these tools are mainly used is marketing; companies use analytics to make advertising campaign decisions and study consumer targeting. With such information, a marketer can improve marketing campaigns, website content, and information architecture.
Preventive maintenance
The use of the analysis can also be applied within the factories in order to check the production in real time and preventive or predictive maintenance of the machinery.