domingo, 13 de maio de 2018

What insights can we get?

maio 13, 2018 Posted by Unknown No comments

What insights can we get?

Financial services

The financial sector stores daily "mountains" of data linked to customer movements . There are myriads of recorded traces through numerous applications, resulting in the perfect atmosphere for information management at the level of excellence - provided you have, of course, robust and scalable software that specializes in data mining . The acquisition of a good data analysis tool enables companies in the financial sector to:

Reduce churn rates

To get an idea of ​​the impact of the exit of clients from the active base of the financial sector, in the USA it is estimated that 30% of clients are vulnerable to migration. Knowing this critical factor, many branch institutions began using data analysis to track the emotional manifestations of account holders (in social media and complaint sites), diagnosing their dissatisfactions in advance, and gaining time to counteract them prior to account closure .
To further understand how Big Data helps reduce your business's churn rate, read the eBook 'How Big Data Analytics Will Predict and Reduce Your Company's Customer Exits' .
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Customize services

Understanding how customers use credit cards and borrowing helps them create products that assertively meet their needs , increasing the potential for attracting new account holders.

Strengthen customer relationships

Solutions in Big Data process all the movements of account holders (from bankline, social media, bank CRM, blogs), in order to generate reports and graphs that reveal the value of the life of each client, their desires and expectations regarding the bank. This allows, among other things, increase cross-selling.
Want to know more insights that Big Data generates for the financial services industry? Then download the eBook 'Big Data in financial services: get to know the applications and cases of success' .
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Retail

The growth of retail data analysis is indisputable . According to an international survey led by GE, 89% of companies see Big Data as crucial to the digital transformation of business, especially in retail. Sales depend on in-depth knowledge of the target audience, which involves the development of a systematic analysis based on high technology. By turning data volumes into intelligence for commerce, you can:

Direct multi-channel marketing actions

With the spread of an increasingly omnichannel consumer, it is necessary to integrate all channels of communication, which involves a full understanding of customer behavior. This market awareness can be achieved through greater segmentation of the target audience, understanding of their consumption habits and preferences, and social and demographic information - all possible thanks to the collection and analysis of data from thousands of consumers.
89% OF THE COMPANIES SEE BIG DATE AS CRUCIAL FOR THE DIGITAL TRANSFORMATION OF BUSINESSES

Add value to loyalty programs

Better understanding of consumer buying behavior is essential to designing truly attractive loyalty programs. V ou already imagine how data mining can contribute in this area, right?
In order to make this question clearer, it is worth mentioning the case of Grupo Pão de Açúcar, which started to use, in 2015, data analysis tools to retain its customers. The system maps out old consumers who have stopped going to the network. It then carries out an electronic survey of the preferred products of each of them.
The discovery of these two factors allows the company to launch customized discount coupons, offering special and distinct promotions to each customer and thus encouraging the consumer to return to the network.

Maximize ROI in marketing

The aggressive market environment requires the application of resources with a "surgical" return to company numbers. So every marketing action must be monitored in real time by social media monitoring tools . If a campaign does not have the expected effect or, worse, it generates negative feedback from the consumer, that failure must be detected quickly in order for the company to take corrective action.
Dig deeper into the benefits of Big Data for the retail industry with the eBook 'Get to know the innovations that Big Data Analytics is bringing to retail' .
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Cheers

"Digital Health" is the watchword in the health sector today. This involves the use of powerful information systems to collect, aggregate and work structured and unstructured data linked to the health sector, generating clinical information that strengthens precision medicine (at the expense of current meta-analyzes, which work with generic and which do not always correspond to the peculiarities of each individual).
Among the many functions that will be mentioned below, data analysis allows the crossing of an immeasurable multiplicity of clinical variables, generating much more accurate diagnoses. According to research by Transparency Market Research, the growth of the Big Data market will be extremely impacting in the coming years. It is estimated that investments in this sector will increase from US $ 6.3 billion in 2012 to US $ 48.3 billion in 2018, and will be mainly managed by the Health sector.
Some benefits that Data Science in the health sector brings to society are:

Prevention of epidemics

Monitoring the manifestations of a population in social networks - in line with the aggregation of field survey data and statistical analyzes - helps to visualize in advance the possibility of an outbreak of an epidemic , giving health institutions time to adjust to sudden increases in demand care and medicines.
INVESTMENTS IN BIG DATE ARE INTENDED TO PASS FROM $ 6.3 BILLION 2012 TO $ 48.3 BILLION IN 2018

The spread of telemedicine and "wearable"

Telemedicine and "wearable" technology are two terminologies closely linked to the dissemination of health IT resources. Telemedicine is distance medicine, propitiated by the use of telecommunications technologies and analysis of large data in the provision of clinical information of patients.
These exchanges of information at a distance are made possible by electronic equipment with high processing capacity, such as gadgets fixed in a patient's clothing (smart watches, bracelets or sneakers, fruits of so-called "wearable" technology).
The exchange of information allows the collection of a larger set of data (Big Data in the area of ​​diagnoses) on the clinical situation of an individual, allowing a more precise debate in the choice of the ideal treatment to be applied to a patient and guiding with greater excellence the procedures linked to health promotion.
The use of these technologies allows health professionals to better understand the pathologies of their patients, provide better research grants and greater credibility to clinical protocols, among other benefits.

Public sector

Decisions by public managers involve difficult daily budget choices, program prioritization, natural disaster prevention and epidemics, as well as infrastructure investments. Organizing all this tangle of strategic action plans based solely on intuition invariably generates administrative collapse.
Big Data for Public Management is the secret of great managers, since there are already data mining tools developed especially for the government area. With Data Science, modern public managers can:

Combat corruption and diversion of revenues

The Ministry of Justice can explain this topic better. Since 2007, this Ministry has been using high-performance data collection and processing systems , crossing information from millions of taxpayers in order to combat money laundering and other financial crimes. The success of the initiative is evidenced by the annual increase in the amount of resources directed to this area of ​​Intelligence.

Strengthen the implementation of "smart cities"

How about having a monitoring system in real time, so that the entire population can monitor the energy consumption and the possibilities of overload in the supply? Semaphores whose synchronization changes depending on the traffic in the streets? Zones with the highest concentration of sound and atmospheric pollution monitored via the system? All this is already possible with the help of Big Data, used in major cities of the world to make them 'smart cities', like Barcelona.
Watch our webinar on Big Data and Logistics and understand how the city of Barcelona has become a smart city worldwide case!

After all, what are the differences between Big

maio 13, 2018 Posted by Unknown No comments

After all, what are the differences between Big Data and BI?

BI and Big Data are somewhat complementary, but not identical. In addition, in general, Big Data is a phase after the maturation of a work with BI. Some distinctions:

Business Intelligence (BI)

  • Focused on the collection, transformation and availability of structured data for decision making;
  • It analyzes what already exists, defining the best hypotheses;
  • Ideal for when you already know the questions;
  • More specific, business-oriented.

big data


  • Focused on the processing of structured and unstructured data, as well as on correlations and discoveries that may result from such processing;
  • It analyzes what already exists and what is to come, pointing out new paths;
  • Ideal for exploring new possibilities, discovering new patterns, and exploring questions that have not yet been asked;
  • Larger, geared not only to business but to any area / segment such as health, entertainment, education.

How are these data transformed into insights?

Big Data solutions "treat" the raw data until it turns them into valuable insights for decision making. They refer to an electronic process that transforms a set of "loose" data into information, information into knowledge, and, ultimately, knowledge into wisdom, that will be used to make the most assertive and expeditious decisions in the context of your business. It is worth mentioning that companies that use Big Data are 5 times more likely to make faster decisions than their competitors and 2 times more likely to achieve superior performance , according to a survey by US business consultancy Bain & Company.
BIG DATA SOLUTIONS "TREAT" GROSS DATA UP TO TRANSFORM IN VALUE INSIGHTS FOR DECISION-MAKING
Now let's make this clearer. Imagine a software developer who needs to understand why there has been an increase in the churn rates of your business. Data intelligence work will come from the basic "traces" of former subscribers, such as contracted plans, recorded complaints, and default rates. Subsequently, this data will generate information as a list of defaulters or which customers expressed dissatisfaction with the software marketed.

It then moves on to the knowledge stage, for example, relating contracted plans with greater possibilities for cancellations (more complete plans are more expensive and more likely to be abandoned in the future than cheap packages). Lastly, the "wisdom" of the business is generated, as the suggestions of actions that must be taken to increase the level of customer satisfaction or make plans more affordable in order to reduce cancellation fees.

Big Data: everything you ever wanted to know about the topic!

maio 13, 2018 Posted by Unknown No comments
Content originally published in the eBook  The definitive Big Data guide for beginners  and upgraded to the blog
The world generates, every day, 2.5 quintillion bytes (1 quintillion equal to 10 raised to the 18th power). The most diverse daily actions of society (from user manifestations in social networks to corporate records and financial transactions) have become valuable data for companies that can use them to better know their customers, understand their buying behavior and even announce a crisis in the industry or migration of customers to competition.
In this increasingly dynamic scenario, having access - before rivals - to market changes is the undeniable threshold between living and dying in the corporate universe. And here's where the secret of success comes in working with Big Data .
A survey conducted by the University of Oxford, still in 2013, already revealed the power of Big Data in modern companies. The survey, conducted with 1,144 managers from 95 countries (including Brazil) showed that 53% of organizations were already using Big Data to understand and improve the customer experience . Even sports leagues, like the NBA , have done it.
The application possibilities of Big Data go far beyond the customer experience, in fact. For example, you can use this technology to increase IT infrastructure security, improve marketing ROI, reduce costs, optimize processes, and even predict market movements before the competition.
Yes, this is possible, and it is not done on the basis of intuition; is the power of IT allied to Statistics, Social Science and advanced mathematical programming. Not surprisingly, a recent study by IDC, a market research and consulting firm, showed that Big Data's global market is expected to grow 600% more than IT by 2018, moving the astounding $ 41.5 billion over the same period.
SECOND IDC RECENT STUDY, THE BIG DATA MARKET MUST GROW 600% MORE THAN IT BY 2018
However, even with its popularization and more than optimistic projections of Big Data's growth for the next few years, some basic questions about the subject are still common. What are the differences between Big Data and BI? How to use data collection and analysis in practice? What types of insights can be generated?
If you also have these doubts - whether you are a manager who wants to take your company into a new age, a professional seeking to specialize in Data Science , a teacher who wants to approach this new technology in the classroom with his students, or simply a curious about it - it's worth investing a few minutes of your day reading this true beginner's guide to Big Data!

Index (or 'what we'll cover in this super article'):

The concept

The term Big Data is as broad as its name implies. To contextualize it and make sense of it, dear reader, there is a brief explanation: we live in an Age in which, (each) year and a half, the same amount of data already created by mankind is generated in all times.
This current epoch, of generating immeasurable volumes of data by companies, people, and apparatus, is called the Big Data Age. The term Big Data also corresponds to the very absurd amount of data currently generated - the "Big Data".
One of Big Data's developments is the term Big Data Analytics , which refers to powerful software capable of handling this data to turn it into useful information for organizations.
Initiatives supported by Analytics enable you to analyze structured and unstructured data, such as call center records, social network and blog postings, CRM data, balance sheets and profit and loss statements. In this way it facilitates the discovery, in real time, of the opportunities that are beyond what human eyes can see in an organic way.
There are several versions about the origin of the Big Data concept, as well as the beginning of its applications. One of the best known refers to NASA, which began using Big Data in the early 1990s to describe huge, complex data sets that defied the conventional boundaries of computing at the time.
In this model, data capture, processing and analysis were done through high impact systems, involving the simultaneous work of numerous sciences. The purpose of these powerful software was to generate knowledge and intelligence from raw data that, alone, could not say.
Prior to Big Data, mathematical formulas, advanced probability and statistical techniques (such as frequency analysis, historical series, and moving average studies) were performed manually - thus dealing with a reduced capacity of variables. With the advent of high-capacity processors and impressive speed, it was possible to transpose all these calculations through software specially developed to turn these "trails" into powerful strategic information to any segment. A Big Data solution works with complex algorithms, aggregating data from diverse sources, relating them, and generating key conclusions for corporate decision making.
Today in Big Data solutions are used by the Treasury to avoid sonegações taxes for the weather to predict natural phenomena at retail to better see the reactions of your customers - you've seen how Amazon uses Big Data ? - by banks to offer personalized services and reduce churn rates (customer exit) for the area to develop attractive products strictly in accordance with what consumers expect ( to name just a few sectors). In short: all areas can take advantage of this technology.

big data

maio 13, 2018 Posted by Unknown No comments

big data

What is and what is its importance?


Big data is a term that describes the large amount of data - both structured and unstructured - that impact companies on a daily basis. But it is not the amount of data available that matters; is what organizations do with them. Big data can be analyzed for insights that lead to better decisions and strategic business actions.

History     Importance
     Who use     How it works
Current Big Data History and Considerations
Although the term "big data" is relatively new, the act of collecting and storing large amounts of information for eventual analysis is very old. The concept gained momentum in the early 2000s when analyst Doug Laney articulated the [now mainstream] definition of the big date into three Vs:
Volume.  Organizations collect data from a variety of sources, including financial transactions, social networks, and information from sensors or data transmitted from machine to machine. In the past, storing them would have been a problem - but new technologies (such as Hadoop ) have alleviated this burden.
Velocity.  Data is transmitted at an unprecedented rate and must be handled in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with data streams virtually in real time.
Variety.  Data are generated in many formats - from structured (numerical, in traditional databases) to unstructured (text documents, e-mail, video, audio, stock quotes and financial transactions).
In SAS, we consider two additional dimensions when talking about big data:
Variability.  In addition to the increasing speed and variety of data, their flows may be highly inconsistent with periodic peaks. What is the latest trend in social networks? Every day, seasonal or event-generated data peaks can be difficult to manage, especially with unstructured data.
Complexity.  Today's data comes from multiple sources, making it difficult to link, match, clean, and transform between systems. However, you need to connect and correlate relationships, hierarchies, and multiple bindings, or you can quickly lose control over your data.
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The big potential of the big data
The amount of data created and stored globally is almost unimaginable and just continues to grow. This means that there is even more potential to extract important insights from this information - although only a small percentage of data is actually analyzed. What does this mean for companies? How can they make better use of that raw information that flows into their walls every day?

How important is the big data?
The importance of the big date does not revolve around the amount of data available to you, but of what you do with that data. You can get data from multiple sources and analyze them to find answers that allow 1) reduce costs; 2) save time; 3) develop new products and optimize offers; 4) make smarter decisions. When you combine big data with high-powered analytics , you can accomplish corporate tasks like:
Determine the roots of faults, problems and defects almost in real time;
Generate coupons at the points of sale, from the customers' buying habits;
Recalculate complete risk portfolios in minutes;
Detect fraudulent behavior before it affects your organization.

quinta-feira, 5 de abril de 2018