Managing data multiplication also means knowing how to use appropriate data analysis tools. Here are the technologies and skills needed to become more competitive and grow the business rapidly
Big data is an increasing amount of information that the digital transformation of the business is circulating in and out of companies. The Big Data, for example, come from the sensors integrated into thousands of objects that are connected to the Net, now we call the Internet of Things; according to the McKinsey Global Institute today there are already more than 30 million, networked and used in the automotive, industrial, public services, or retail sector and the number rises every year by 30%.
Beyond the data flows produced by information systems and infrastructures supporting the production, distribution, and provision of services, big data is a phenomenon associated with a massive evolution of people's habits and habits. Every time we use a computer, we turn on the smartphone or open an app on the tablet, always and anyway we leave our fingerprint made of data.
Big Data Analytics: from the browsers to the society what is the meaning?
The Big Data, in fact, are also increasingly pushed by multimedia that originated by the proliferation of fixed and mobile devices we use to live and to work. The familiarity with video sharing and a culture of an image that leads people to share all kinds of photo shoots will help those who will manage this amount of data to understand even better tastes and trends, directing better decisions.
Big Data also comes from social media, and from all the traffic of opinions and thoughts that passes through the various CRM systems, from the cash desk of a supermarket that crawls a loyalty card to a phone call that arrives at a call center.
In fact, unlike many technological trends, Big Data is not a trend but a management need. And they are for any type of organization. Those growing data sets that seem to blow up corporate databases will be the keys to competitiveness, business growth, and innovation. How?
- helping to understand the reactions of the markets and the perception they have of brands
- identifying the key factors that move people to buy a certain service or product
- segmenting the population to personalize action strategies as much as possible
- enabling new experiments allowed by the availability of unpublished data
- gaining in predictability, thanks to an information history so wide-ranging and punctual to allow simulations far more than likely
- enabling new business models
Also in Italy, the Big Data market grows
Big Data Analytics in health, which continues the positive trend of the last three years also in 2018, reaching a total value of 1.393 billion euros, up 26% over the previous year. (Source: Big Data Analytics and Business Intelligence Observatory - Milan Polytechnic). In fact, the business is there and it shows.
What are the technologies for Big Data Analytics?
In 2018, 45% of spending in Analytics is dedicated to software ( databases and tools to acquire, process, view and analyze data, applications for specific business processes ), 34% to services ( software customization, system integration) company information, consultancy on process redesign ) and 21% on infrastructure resources (computing, server, and storage capacity to be used in the creation of Analytics services).
Examples and state of the art of Big Data
Most people have only a vague idea of how much Google has a deep understanding of everything we search online, or how much Facebook knows (about everything and more) about friends, feelings, preferences, dreams, and needs of its great community?
Even if we have never told him, Google knows how to recognize our generality, profiling us on the basis of our browsing methods, to propose absolutely targeted advertisements to follow custom tailor made personalization. For all that half of the sky that has chosen Android, MountainView always knows where we have been, where we have traveled, stopped, eaten or stayed.
Facebook, however, with its one billion subscribers, even knows when a love story has reached a critical point. Based on the status updates of the bulletin boards (3.3 million posts are published every minute), the company can predict if a relationship is bound to last, with disturbing precision. Not to mention Twitter that moves every 347 seconds 347 thousand tweets and has developed an API (Application Program Interface) that allows third parties to access each of them (by definition all public): it is unstructured data, plumbed by new techniques of sentiment analysis that are able to understand the emotions contained in the textual information, helping decision makers (business and politicians) to understand where the wind of public opinion goes.
But it's not just Google, Facebook or Twitter that tracks our digital actions: Big Data is the lifeblood of Bing, Yahoo, Amazon and any Internet Provider that knows the pages we visit at all times (even when we believe we do it in hidden mode).
Examples of Big Data in the world
Turning to public order, smart cities are becoming a shining example of Big Data Management and Big Data Analyst. Thanks to the sensorized streetlights, the PA manages to better manage traffic peaks and monitor pollution. The police can rebuild the suspect car trails by analyzing CCTV cameras increasingly omnipresent outside the premises and banks. For the separate collection, RFID tags are used to make connections and communicating bins, tubs, and bags.
According to the McKinsey analysts, in Europe the public administrations with good management of Big Data can obtain savings in the order of 100 billion euros, increasing operational efficiency. A figure that could increase dramatically if Big Data were also used to reduce fraud and errors, achieving fiscal transparency.
Researchers found retailers using Big Data have increased their margins by 60%. How?
Analyzing the purchasing behavior, or the receipt, associated with the loyalty card and the various interactions with promotions, announcements, e-mail marketing, any newsletters you receive periodically and periodically open. All this represents a mountain of information to collect and analyze to define an increasingly tailor-made offer. From the point of view of the services associated with geolocation (beacon, NFC, app, interactive touch points) generate Big Data that, if well managed, according to experts would generate something like $ 600 billion favoring a surplus consumption.
Big Data Management means going beyond order processing, implementing new systems to support marketing campaigns and better managing loyalty programs by monitoring feedbacks recorded by each individual promotion, product launch, initiative but also by managing the warranty claims or complaints, reaching a 360-degree view of customers, products and any commercial operation.
Digital markets are also conversations
The issue with Big Data is not so much their quantity as the ability of companies to be able to analyze the available data in the correct way. The formula is conversational and develops in three stages: interrogation, response and detailed vision . More and more sophisticated algorithms allow us to intercept and interpret every digital stream that is running or has traveled the Net. This is the technological progress that is revolutionizing business models.
"Most companies are capturing only a small portion of the potential associated with Big Data - underlines Alessio Botta, a partner of McKinsey & Company, responsible for advanced analytics for the Mediterranean area. The reason is not only a budget problem associated with the necessary investments but also, and above all, of skills. On the market, there are still few Big Data managers able to enhance the information and data present in the company ".
As the experts explain, the scope is still new and the ability to embrace multiple levels of information and multiple horizons of analysis requires a preparation that still has no history. Not only that: we need interpersonal, communication and leadership skills, teamwork attitude, analytical skills, and problem-solving skills.
To this end, McKinsey's latest report ("The age of analytics") identifies four types of profiles that will be increasingly requested by companies:
- data architects, ie those who design data systems and their workflows
- data engineers, able to identify solutions based on data and to develop targeted scouting and analysis products
- data scientists, who analyze data thanks increasingly sophisticated algorithms
- business translators, bimodal figures who have technical knowledge and skills related to the business