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Big data: what they are and why you can’t ignore them

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The use of digital technologies has turned out to be a real gold mine for the production of a valuable resource: data generation.

Devices that are always connected (IoT) and easy to use, increasingly intelligent production processes, ever wider digital transformation combined with a reduction in costs, have lowered the threshold of access to these technologies, making them available to all users. At the same time, the development of analytical platforms and algorithms based on machine learning and artificial intelligence have made it possible to transform this mass of information, for example consumer habits and behaviors, into valuable and useful data for companies.

The development of the IoT and IIoT (Industrial Internet of Things), which uses sensors to improve people’s lives and business processes, is also data-driven.

The Digital transformation allows you to transform every touch point, digital contact, whether it is a totem in a railway station or a website or a newsletter or high in a valuable source of information, a real mine of data.

The large amount of data, structured and above all unstructured, generated by digital technologies are Big Data. Unstructured data because video, text, audio and any other digital track are currently widely used and form the company’s big data.

Mature companies already exploit this new resource to improve the offer of their products and services, optimize costs and resources, reduce waste, devise new marketing strategies, increase customer retention, predict new market trends and exploit them to your advantage.

What can you do with big data?

Big Data are therefore the raw material needed to generate new knowledge, useful for making more informed decisions and implementing the best actions/ strategies.

By integrating these data with the basic information assets (most of the times little used, or used only to make descriptive analyses on past events) companies can carry out advanced analyses with predictive and/or prescriptive purposes, with a significant impact on multiple business processes (Advanced Analytics).

big data per management e data analytics

How to extract value from big data?

To get new value from Big Data you need:

  • the right technology infrastructure such as data warehouse, data lake, cloud systems rather than on premise;
  • proper management of business processes in a “data-driven” environment;
  • introduction of Business Intelligence & Analytics in systems capable of integrating analysis models and algorithms of Machine Learning and Artificial Intelligence;
  • business analytics and data science skills to develop the project.

At this point the data integration and data visualization tools (e.g. SAS, Qlik, Dataiku, Azure Machine Learning, etc.) will do the rest, providing the user manager with simple and intuitive analysis dashboards, to allow him to do in-depth analysis without any IT expertise, focusing exclusively on the aspects important to his business.

What does this mean? Immediately obtain all the information to decide how to improve an aspect of your business or a specific business area (sales&marketing, finance, production, logistics, etc.) basing your decisions on reliable data and algorithms and concrete scenarios.

The 5v of Big Data

To date, big data capable of generating value are catalogued according to the 5v model:

  • Veracity- reliable data.
  • Volume– high mole (constantly growing).
  • Velocity- data is generated and captured in real time.
  • Variety- data from different sources, in different formats, even unstructured.
  • Variability- their meaning changes depending on the context.

In order for big data to express its potential, it is necessary that it is managed in a global project, where the various business departments are no longer analyzed in compartments, but share their information in a single system capable of creating connections, to allow deep data exploration, to bring out unpublished information, which would otherwise remain hidden in an insignificant amount of data. An appropriate data lake or data hub on which to base the consolidated concept of datawarehouse or specialized data mart.

How can companies increase their profits with Big Data?

Thanks to Big Data and a Business Intelligence & Advanced Analytics project, any company, even small, can achieve its business objectives and see its profits grow.

Cloud Computing and innovation allow today to bring these technologies to the market for small and medium enterprises. According to the Big Data and Business Analytics observatories of the Politecnico di Milano, 44% of Italian SMEs have increased awareness of the need to analyze and exploit the data collected. To manage the Digital Divide as a possible cause of a deep selection on the market, topic that we will deepen in another article.

For example, a deep knowledge of your customer, his buying habits, the timing and uses of the product, enriched by other data about travel or consumption preferences, allows a greater profiling of your audience, therefore to act in a targeted manner on levers that improve the degree of satisfaction by increasing engagement with customers and customer-retention.

Similarly, integrating business data with market forecasting and behavior trends can provide important information to be used to increase sales or broaden the offer by introducing new products/services that are sure to succeed. Even to identify new markets.

Another way of success is to implement cost reduction strategies, for example by integrating preventive and even better predictive maintenance systems. If manufacturing industries were the first to integrate Advanced Analytics solutions to extend the life of their machines and increase their economic return, today predictive maintenance is also a reality in sectors such as logistics and transport, in the world of luxury and fashion, and in the hospitality industry.

In the Hospitality sector, for example, the use of Big Data is already a reality thanks to Business Intelligence projects that allow the generation of a dynamic pricing strategy in real time, for example, taking into account demand, supply and availability, integrating the analysis with other data from external sources, such as the main OTAs, traffic data, tourist flows, etc.

Or just think that the Internet of Things (IoT) is already widely used by the manufacturing sector, which then uses the Big Data generated by sensors and interconnected devices to implement the best energy efficiency strategies, cost reduction and zero waste.

The real challenge of the future will no longer be to be able to give answers to business questions (Augmented Analytics systems will make this process simple), but to ask the right questions, investigate unexplored aspects and find new and hidden insights, maybe before others.

We realize Business Intelligence & Advanced Analytics solutions to transform simple data into information of freat strategic value.

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