When we talk about Big Data we are referring to data sets or combinations of data sets whose size (volume), complexity (variability) and growth rate (speed) make it difficult to capture, manage, process or analyze them using conventional technologies and tools. The concept of Big Data and its relevance will be fully explained.
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INTRODUCTION.
Today information is generated at an enormous rate, from many points of view and in many ways, information is generated anywhere in the world, at any time, this same information that is generated flows itself throughout the world becoming a sea of information to process.
Similarly, within organizations, information is generated from all points of the organization, such as in the sales, project, production, logistics, maintenance, quality, cost, and finance departments. to mention a few, and it is of utmost importance not only to store this information that can help us to one day review a production history for example, not only should it be used for that, but also for decision-making, which is something very important.
There are techniques and software that help us with this task, that's when big data comes in, which helps us not only to gather information but to be able to assimilate, manage and control it, to make sense of it all, to be able to make key decisions regarding consumer behavior for example, or also with respect to the projection of sales of an organization, knowing how many people will complete their studies at a university and if we are ambitious until we know what will become of the future of others.
This article will discuss more about all that big data implies, its applications, success stories, as well as the benefits of using this
tool within organizations.
Big data
When we talk about Big Data we are referring to data sets or combinations of data sets whose size (volume), complexity (variability) and growth rate (speed) make it difficult to capture, manage, process or analyze them using conventional technologies and tools, such as as relational databases and conventional statistics or visualization packages, within the time necessary to be useful. (PowerData)
The volume of data to define big data is not yet firmly decided, although we know the term, experts still do not define exactly how much information can be equivalent to big data, some experts stipulate that a volume of between 30 and 50 terabytes can already be considered as such, the value changes over time.
Importance of Big Data
What makes big data so useful is that it can help to provide benchmarks to an organization, by handling large volumes of information, all of it can be molded or tested in any way the organization desires and therefore helps organizations to have a better response time, in the same way the problems can be identified in a clearer way.
By conducting massive data collection and conducting trend searches on data, it helps organizations move faster, more efficiently and more effectively. It also allows them to find the most problematic areas so that they can be removed before the problems become much greater.
The most successful companies with Big Data achieve value in the following ways:
- Cost reduction. Big data technologies like Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data, as well as identifying more efficient ways of doing business. Faster, better decision making. With Hadoop speed and in-memory analytics combined with the ability to analyze new data sources, companies can immediately analyze information and make decisions based on what they have learned. New products and services. With the ability to measure customer needs and satisfaction through analytics comes the power to give customers what they want. With Big Data analytics, more companies are creating new products to meet customer needs. (PowerData)
Sectors where Big Data is used
Tourism: Keeping customers happy is key to the tourism industry, but customer satisfaction can be difficult to measure, especially at the right time. Resorts and casinos, for example, only have a small chance to turn around a bad customer experience. Big data analytics gives these companies the ability to collect customer data, apply analytics, and immediately identify potential issues before it's too late.
Healthcare: Big Data appears in large quantities in the healthcare industry. Patient records, health plans, insurance information, and other types of information can be difficult to manage, but they are full of key information once analytics are applied. This is why data analysis technology is so important to healthcare. By analyzing large amounts of information - both structured and unstructured - quickly, diagnoses or
treatment options can be provided almost immediately.
Administration: Administration faces a great challenge: maintaining quality and productivity with tight budgets. This is particularly problematic with regard to justice. Technology streamlines operations while giving management a more holistic view of activity.
Retail: Customer service has evolved in recent years, as
Smarter shoppers expect retailers to understand exactly what they need, when they need it. Big Data helps retailers meet those demands. Armed with endless amounts of data from customer loyalty programs, shopping habits, and other sources, retailers not only have a deep understanding of their customers, but can also predict trends, recommend new products, and increase profitability.
Manufacturing companies: These deploy sensors in their products to receive telemetry data. Sometimes this is used to offer communications, security and navigation services. This telemetry also reveals usage patterns, failure rates, and other product improvement opportunities that can reduce development and assembly costs.
Advertising: The proliferation of smartphones and other GPS devices
offers advertisers the opportunity to target consumers when they are close to a store, cafe or restaurant. This opens up new revenue for service providers and offers many companies the opportunity to get new leads. (PowerData)
Most relevant Big Data applications. Navigation between the information.
Big data is an essential tool for organizations to make decisions to improve their performance, minimizing the risks they face in the process, giving more effectiveness to any operation that is carried out. For this it is necessary to implement a good navigation in the data that does not give big data in the business and it is necessary to do it complying with three immovable aspects:
- They must be large volume data. They must provide variety. Quick access.
By conveniently navigating this data, the organization will be given greater effectiveness, leaks will be minimized, and any type of problem we may encounter can be fixed.
Warehouse increase.
Another application of Big data is that it helps us so that a warehouse structure that is already in place can grow with better results. This helps more data of different types to be optimized and better stored in the warehouse. This helps to obtain different advantages such as being able to have new points of view that were not available before obtaining this data.
Analyze operations.
In this process, it is possible to find out which anomalies are constituted to immediately measure the operations. Work is done to ensure that the infrastructure is protected and that there are no serious problems in the service such as that which would be a blackout. Using operations analysis, big decisions can be made in the organization, observing how structured data is and what is happening within the business.
Increase security.
Due to big data we are able to not only observe where the security holes are, but it is also possible to prevent future risks by checking the oscillation that is hidden behind external and internal data. With security it is possible to apply different procedures that lead to enjoying applications such as real-time analysis, checking online traffic for attacks and conflict prevention by reviewing the data that passes through the structure.
What data should Big Data explore?
According to (Fragos, 2012) These are the types of data that big data should explore.
1.- Web and Social Media: It develops web content and information that is acquired from social networks such as Facebook, Twitter, LinkedIn, etc., blogs.
2.- Machine-to -Machine (M2M): M2M represents the technologies that agree to link to other devices. M2M uses connectors such as sensors or meters that capture a specific event (speed, temperature, pressure, meteorological variables, chemical variables such as salinity, etc.) which are transferred through wired, wireless or hybrid networks to other applications that they convert these events into specific information.
3.- Big Transaction Data: It contains log observations, in telecommunications defined records of calls (CDR), etc. This transactional data is usable in both semi-structured and unstructured formats.
4.- Biometrics: Biometric information containing n fingerprints, retinal scan, facial recognition, genetics, etc. In the area of security and intelligence, biometric data has been significant information for investigative agencies.
5.- Human Generated: People generate various amounts of data such as the information stored by a call center when establishing a phone call, voice memos, emails, electronic documents, medical studies, etc. (Fragos, 2012)
Real examples of the use of Big Data.
According to (BBVA, 2015) in recent years, we have found some very striking examples in the use and analysis of Data and Big Data that, in some way, are worth both to create new products and to forecast behaviors and trends, improve management of marketi ng, etc. We emphasize the following:
Macy's and its prices in real time
Macy's is one of the largest retailers in the United States, noted for its e-commerce. Using SAS Institute technology, you have been able to improve your income and user experience. Thanks to the speed of analysis and the reports obtained with this new technology, they have reduced the annual cost of analytics by $ 500,000. Macy's today perfectly knows the impact of its newsletters and notifications and knows the most satisfied customers better, what they like and what they don't… Today, the use of this data allows them to segment their shipments as much as possible, so they send less emails, but with much more impact and have managed to reduce subscription rates by up to 20%. Thanks to the use of an algorithm and the control of demand and inventory, they can launch cross offers,adjust prices and do almost real-time for your 73 million items for sale.
Ball games and millions of data
Almost everyone has heard of the movie Moneyball: Breaking the Rules (2011), if not for Brad Pitt, at least as an example of the use of Data. It happened in the 2002 preseason at the Oakland Athletics of the United States Major League Baseball. Sports manager Billy Beane revolutionized the history of the club and possibly the sport in general after signing a young economist, Peter Brand, who brought new ideas. Together they hired undervalued, but economically profitable players with very different selection criteria. The scouts' intuition and wisdom is replaced by the conclusions of the statistics and accumulated numbers analysis when establishing the needs of the team and the players that best adapt to them.
Currently we have many more cases in which Big Data is used in sports. NBA teams have already implemented the use of data when preparing game strategy, while the NFL has a platform that helps 32 teams to make the best decisions based on data analytics with their applications.: from the state of the surface of the grass to the weather conditions, going through data from the university stage of each player… everything is registered and everything can be used to draw different conclusions, such as preventing injuries to players. In addition, it analyzes the preferences of fans thanks to its NFL Now application, which offers the possibility for them to create their own channel with varied NFL content: funny videos, favorite cheerleaders, team information,by players, etc. They also use NetApp to store all of this data. With this they manage to establish the demands of the fans and make things easier when it comes to establishing marketing actions, expanding the market, finding the most appropriate partners, etc.
Obama's reelection
After his first term, US President Barack Obama decided to use Big Data for his reelection in 2012. About a hundred people worked in the campaign's analytics department. 50 were fixed in the central offices, another 30 were mobilized throughout the different headquarters of the country, and 20 were solely and exclusively focused on the interpretation of the data received. After a first analysis, the campaign's efforts were
They focused on three aspects: registration (collecting data from convinced voters), persuasion (addressing the questionable in an effective way), and electorate voting (making sure supporters went to vote yes or yes). And, for the first time, the three most important teams of the electoral campaigns: the field, the digital and the communication, worked with a unified strategy with the respective data of each one. The engine of everything, the smart platform used was HP Vertica. Among the most effective actions that this platform allowed were: collecting data at the field level and making very fast feedback via email notifications by the online team (improved in time and efficiency);or detect the niches in which TV advertising would work better by crossing voter data with other demographics, audiences, advertising prices, programs… (improved in impact and segmentation). With their analysis, the Obama team optimized communication and improved the response of the related electorate, allowing not to waste resources, time and money on voters who were not supporters of his party.
BBVA: Mobile World Congress and Turismo Madrid
BBVA has also carried out various Big Data tests, in which importance has also been given to their visualization to allow them to be more understandable in the eyes of a neophyte viewer. In Barcelona in 2012, the economic impact of the Mobile World Congress was measured. To do this, data was extracted from transactions made with credit cards, both the week before and the week in which the event took place. The results serve to conclude the places, days and times where there was the most “movement”, something that, for example, can help businesses to reinforce their marketing and sales actions in the face of similar events or the cities themselves to do the same with its tourist promotions.
Another example of a study would be the one carried out by BBVA in which the use of credit cards in Spain during Easter 2011 is analyzed in four sectors: markets and food, bars and restaurants, fashion and gas stations.
A last example of the entity was carried out together with the Madrid City Council which, under the title Tourism Dynamics in the City of Madrid, analyzes the behavior of tourists in terms of their commercial activity during 2012. Among the many results The study served to quantify the economic impact of Gay Pride in various areas of the city. Commercial spending increased 24% compared to the same week the previous month. In addition, other interesting data such as the tourists who spend the most, what they spend, where they move, etc. are known.
Data and Big Data are changing many things, not only when making business, sports, political or other decisions, but also when creating products, innovating, storing data, developing, visualizing things… It is a trend that has become widespread and that seems to
stay with us for a long time. (BBVA, 2015)
conclusion
As we could realize, Big Data has become an important tool for decision-making in large organizations, this tool helps us not only to reduce costs and increase our way of deciding within the organization, but also helps us to have greater security in those decisions we make, backed by industrial amounts of information that supports each decision made and also benefits us by having greater control of what we want for the organization, its great permeability helps it to be used in all types of industry and organization. Big data is today, without a doubt, a potential tool that can change the course of any organization that uses it responsibly and wisely.
Thesis proposal.
Make a search engine for specific services and merchandise using Big Data.
Overall objective.
Provide the user with a simple and easy way to find what they want or need from a product to a service through a search engine that obtains information based on the data generated from the organizations and maintains inventories in real time.
Thanks.
I thank my mother who is the strength to continue every day and who has made me get to where I am, my teachers who have given me their time and knowledge to continue my studies, Doctor Fernando Aguirre y Hernández since He has given us all his experience and knowledge in this matter of Fundamentals of Administrative Engineering, as well as CONACYT since he gives us his support to motivate us to get ahead in our adventure for masters.
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Fragos, RB (June 18, 2012).
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