The new trends in analytics focus on even faster processing and above all on the quality of the result, moreover they must first of all rely on data that is correct and controlled from the beginning. Having a large amount of information available does not in itself offer the security of obtaining the answer you are looking for in the expected time.
The challenge is to put in place the best technological tools with the best skills to be able to govern the data that already today are available to companies and present in data warehouses with those that are the largest and most effective. network collects from the connected objects.
These huge amounts of data, or Big Data, can be defined as an important amount of information resources collected, stored and managed by different technologies, which require fast and cheap processing methods and that allow obtaining detailed information useful for decision-making processes and to the automation of activities.
The management of the data lifecycle becomes essential in order to be able to respond to the needs of the business and to give a meaning to those that constitute the information assets of a company, without forgetting the regulatory obligations regarding the safeguarding of data quality and privacy to which today all companies are required to respond.
Gartner offers a summary of what a Big Data system should be, that is to say those that in slang are called the 5 Vs: Volume, Speed, Variety (traditional assets), Value, and Truthfulness (new assets).
The Kirey Group vision of big data is built around these assets, which has implemented a structure to manage and monitor the data lifecycle, from the birth on the source systems to the arrival on the database and the processing of information.
“The term used to indicate the diversified mass of unstructured data that is collected is datalake,” explains Valter Cavallino, Senior Information Management Manager, Application Analytics, Kirey Group’s BI tools, “an image that concretizes the concept of a container that collects all the information of the companies in a silos of disintegrated data, still without form, liquids. We need specialized skills to design this area of unstructured data and then to bring the information to the surface and bring it to a data warehouse “. Just like sand in a lake, data is deposited and waiting to be made to emerge. The task of the Kirey Group data engineers is to identify the data useful for providing answers to specific questions and to give them an organized form: “we make the relevant information emerge for the users of the company according to the interest, the level of data structuring is defined based on the needs of the various sectors and company levels and the information is aggregated into layers that can be used by the company operator ”.
The traditional big data technologies can find further strength, further minimizing the time-to-market of the solutions, through the adoption of data virtualization technologies that allow to model one or more data layers of the big data solution in a more streamlined way than to traditional technologies. The data resides in a single point and remains in fact certified. Last but not least, the opportunity of cloud services that guarantee the customer high standards of security and disaster recovery, as well as a very high scalability that becomes just a click away.
Skills for reading Advanced analytics
The large amount of data present within a datalake, their complexity and the speed required to process and extract information and phenomena within it, increasingly requires the intervention of professional figures with specialized skills different from the traditional figures that can be found within an IT department.
The companies that offer information management services are today expanding their offer to include forms of service that favor the ability of the client company to use the information gathered as much as possible: “we realized the need of our interlocutors to be able to rely on a partner capable of managing strategically above all an information system, through the analysis of the situation and the implementation of a technologically innovative architecture capable of providing full control of the data. We started, with our Kubris innovation center, to train people with mathematical and statistical backgrounds, and to use innovative technologies such as machine learning in our projects “. Figures like the data scientist or the machine learning expert work in collaboration with whom within the company knows the business logic of the business to search the datalake for information useful to the objective and to give them the correct and easily legible form.
The circle of big data ends with the truth and value of the data. Ensuring data quality is a complex challenge: using data does not lead to a solution if the information it contains is incorrect. The data, therefore, before being used must be subjected to a “control system that provides indexes to verify the robustness of the whole process”, explains Cavallino, an analysis modality that is able to reconstruct the history of that data and its components.
Thanks to the experience gained, the Information Management team of Kirey Group has developed a suite of products, DG Suite, in order to provide a single product that supports the user in the data monitoring, management and reporting processes. Based on IQF metrics, the suite allows you to design the controls necessary for data monitoring and collect the results of the analysis to calculate the robustness of a control system; it also allows implementing actions to improve data management processes and to produce reports compliant with current regulations and regulations.