Where is Big Data used?
Big data is used in Marketing, politics, health, sports… The applications are endless. We analyze its possibilities with some examples
What examples of big data can we find in companies?
Big Data is a term used to define a large data set or combination of these. The storage, observation and data processing to obtain information relevant is widely spread today.
Our daily life is affected by the use of Big Data as, for example, in the suggestions that show us applications like Spotify, Netflix, Amazon, Twitter, Facebook, etc. Behind all of them are Machine Learning algorithms that process the data related to our actions in those platforms and that, based on them, generate suggestions for us.
Marketing and Sales
Customer data is analyzed and processed obtaining information related to your tastes, preferences or behaviors.
Thus, they can be classified or segmented into different categories and use predictive models so that the organizations may have indicators of acceptance of their products, potential sales, etc. Ultimately, play crucial role in the development of marketing and sales.
Finance
The development of Big Data in the financial field is being vitally important in recent years. Among the advantages found in this alliance we highlight the simplification number of steps and cost reduction to process data. Also, Big Data provides knowledge for decision making financial. Likewise, it evaluates the risks of the investments and It allows a more accurate monitoring of the data.
For the fight against crime
In the United States, the security forces and bodies have of applications that, using Big Data, can predict
the probability of a crime occurring in an area determined. With this they have developed the so-called Atlas of
Risk (Smart Steps app in Massachusetts).
Sports
In the NBA and the NFL, applications that make use of the Big Data to define the strategies to be used in each game, prevent player injuries, know the preferences of fans etc.
Politics
Before the 2012 US elections, Obama decided together with his team to use Big Data during the campaign
electoral process to analyze the data they accumulated from potential voters. They concluded that, in order to win, they had to focus on targeting doubtful voters in a effectively and, at the same time, influence voters to
convinced Democrats were to vote.
They used the HP Vertica platform, which allowed them to obtain data, efficiently and quickly report information,
and segment potential voters. In this way, they were able determine which ones would be more receptive to TV advertising, newspapers, social networks… The field team, the digital one and the of communication worked with a strategy based on the data obtained, thus achieving his re-election.
Telecommunications
Some mobile phone operators use Big Data to analyze what is said about them on social networks, examine
data from your customer support tickets or complaints.
This makes it possible to implement strategies that reduce the number of portability or increase the capture of
New customers.
Big Data in Health and Healthcare
Both in the pharmaceutical industry in the field of investigation of new drugs as in the diagnosis of diseases, it is becoming more widely used the processed of the collective Big Data (medical history, genetic material,
prediction of hospital readmissions…) to optimize and test models that improve the results, facilitate the tests in the clinical trials with new therapies or improve diagnoses. Big Data is also useful for more administrative management health efficient.
The importance of Big Data
Big Data, why is data analysis essential?
There is no doubt that Big Data is a concept of growing popularity and many companies claim to use it.
However, many organizations are not prepared, either due to ignorance or lack of training in this regard.
It is important to know what Big Data is and why it is needed, but if you really want to know why it is essential
data analysis in your own company, continue reading.
Importance of Big Data Analytics
Data is essential in today’s business fabric and are becoming a key piece that helps take strategic decisions. You should know that they are generated daily, for both users and companies.
Big Data analysis is a revolution within information technology. It is useful for companies because it answers many questions that some of them unknown, allowing to identify customer problems.
If you divide the data analyzes according to the nature of its environment you find three types: descriptive analysis, the predictive and the prescriptive. This type of analysis requires of both quantitative and qualitative techniques to improve productivity and profits of companies.
What are the benefits of Big Data Analytics in real time?
The techniques and tools to analyze Big Data are suffering a clear increase in demand due to the value that
they have for organizations. Companies can find opportunities to gain new knowledge with which manage them efficiently. This information is helpful undoubtedly to provide meaningful information with which make smarter and better business decisions.
Any company can enhance its strategies, but if takes into account the approach of customers and the target audience, these will improve. An efficient Big Data analysis is useful because it works towards improving business profits.
Benefits of Big Data Analytics
There are some data analysis tools that reduce the cost of storage. This is significant because it increases business efficiency. Furthermore, thanks to these tools analytics is simpler, leading to decision making decisions that save energy and time, when carried out with greater speed.
What other benefits can you find?
The service improves. A circumstance that will generate a higher conversion rate and additional income. If there is an error in the organization, it will be known in real time, which will minimize its effects on operations and
prevent a client from stopping using those products. Improvement in decision making. By having a large volume of structured data available, organizations can make decisions based on their interpretation with greater speed and criteria. Market knowledge. It helps you make decisions and allows you to locate windows of opportunity, thus anticipating the needs of consumers and consumer trends or imbalances in customer service. Real time feedback. Big Data not only allows us to store or process a large amount of data, but also makes it easier to
receive it and have that information available more quickly. It is very agile and allows you to know the status of a launch or the result of a strategy immediately. Present and future technology. Big Data is evolving and in the not too distant future it will be essential to make decisions. This is the reason why companies are betting on digital transformation. In sectors such as medicine or the financial sector, it is assuming a revolution. For all these reasons, data analytics is one of the most important issues in today’s business.
Are new job opportunities opening up thanks to Big Data?
Those professionals who have the ability to analyze the Data is in high demand, as investment in technology
of Big Data is of general interest.
Today’s companies offer very attractive incentives to best-qualified professionals in this field. The data administrators, IT professionals, or engineers They can develop a very promising career. Some of the
most valued titles are solution architect, data analyst Big Data, business intelligence consultants, software engineer Big Data, etc.
The nature of the work will differ depending on the industry.
Why is data analysis important?
In short, the analysis of Big Data is a trend to the unstoppable rise, in which more and more are demanded
professionals. Compiling and interpreting this data is very important for the value chain of a company and offers you different perspectives. Using analytics will improve knowledge of each industry, because the experts who are dedicated to study the Big Data offer new conjunctures to find and learn about the different business opportunities that are they can pose.
The companies that use the tools aimed at analysis of Big Data in the different industries obtain great benefits when used properly.
Big Data, why is data analysis essential?
There is no doubt that Big Data is a concept of growing popularity and many companies claim to use it. However, many organizations are not prepared, either due to ignorance or lack of training in this regard.
It is importantif takes into account the approach of customers and the target audience, these will improve. An efficient Big Data analysis is useful because it works towards improving business profits.
Benefits of Big Data Analytics
There are some data analysis tools that reduce the cost of storage. This is significant because it increases business efficiency. Furthermore, thanks to these tools analytics is simpler, leading to decision making decisions that save energy and time, when carried out with greater speed.
What other benefits can you find?
The service improves. A circumstance that will generate a higher conversion rate and additional income. If there is an error in the organization, it will be known in real time, which will minimize its effects on operations and prevent a client from stopping using those products. Improvement in decision making. By having a large volume of structured data available, organizations can make decisions based on their interpretation with greater speed and criteria. Market knowledge. It helps you make decisions and allows you to locate windows of opportunity, thus anticipating the needs of consumers and consumer trends or imbalances in customer service. Real time feedback. Big Data not only allows us to store or process a large amount of data, but also makes it easier to
receive it and have that information available more quickly. It is very agile and allows you to know the status of a launch or the result of a strategy immediately. Present and future technology. Big Data is evolving and in
the not too distant future it will be essential to make decisions. This is the reason why companies are betting on
digital transformation. In sectors such as medicine or the financial sector, it is assuming a revolution. For all these reasons, data analytics is one of the most important issues in today’s business.
Are new job opportunities opening up thanks to Big Data?
Those professionals who have the ability to analyze the Data is in high demand, as investment in technology of Big Data is of general interest.
Today’s companies offer very attractive incentives to best-qualified professionals in this field. The data administrators, IT professionals, or engineers They can develop a very promising career. Some of the most valued titles are solution architect, data analyst Big Data, business intelligence consultants, software engineer Big Data, etc.
The nature of the work will differ depending on the industry.
Why is data analysis important?
In short, the analysis of Big Data is a trend to the unstoppable rise, in which more and more are demanded
professionals. Compiling and interpreting this data is very important for the value chain of a company and offers you different perspectives. Using analytics will improve knowledge of each industry, because the experts who are dedicated to study the Big Data offer new conjunctures to find and learn about the different business opportunities that are they can pose.
The companies that use the tools aimed at analysis of Big Data in the different industries obtain great benefits when used properly.
Big Data, why is data analysis essential?
There is no doubt that Big Data is a concept of growing popularity and many companies claim to use it.
However, many organizations are not prepared, either due to ignorance or lack of training in this regard. It is important to know what Big Data is and why it is needed, but if you really want to know why it is essential
data analysis in your own company, continue reading.
Big data analytics and IT optimization
Big data analytics refers to the process by which takes the raw, opaque data and converts it in an easy to understand and use resource. the opaque data is the data that companies collect during the activities usual commercial, and that they must store and protect by compliance reasons. We often give little importance to data, but like the others, they provide useful information that you can use to improve your business.
The information provided by big data makes it possible to avoid problems rather than having to answer to them. Analyze data patterns help predict behaviors and customer needs instead of guessing them, which can translate into increased revenue.
To be effective, the analysis software must be running on a reliable, comprehensive and flexible basis. Therefore, the IT optimization is critical. You must make sure that may continue to collect, analyze and use your data at as your tech stack changes.
Data lakes, data swamps and big data storage
Data lakes are repositories that store copies exact or near exact information about your data in a single location, and are increasingly common in companies that prefer a extensive and comprehensive repository for them. Also, they are less expensive than databases.
Data lakes maintain an overview of your data, so that your best analysts examine their techniques of refinement and analysis outside of storage traditional (as a data warehouse) and independently to any registration system (the name of a source of authorized data of a particular data element). If you want that its most qualified analysts continue to hone their skills and exploring new ways to analyze data, you need a data lake.
Data lakes require ongoing maintenance and plan that defines data access and use. Without this maintenance, you run the risk of them becoming inaccessible, difficult to manage, expensive and useless. The data lakes that users cannot access called «data swamps».
Large companies have multiple business units, each with their own information needs. Each of those units must compete in some way to access infrastructure and data in order to analyze them, which represents a problem of resources. The lakes do not solve the problem. What you need is a multitenant workload isolation with a context
of shared data.
What does this all mean?
Basically, instead of making a full copy of your
data each time a new business unit needs access
(which implies that the administrator writes scripts to
copy them and make them work), this solution allows your
company reduce the number of copies needed and share them
in all units by organizing them into containers and
virtualization of data analysis tools.
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