Big Data is large amounts of data that will be impossible to process or analyze using traditional methods using PCs and human labor. The peculiarity of Big Data lies in the fact that the data array grows over time, so huge computing power will be needed. To process this data, it is necessary to use innovative methods of information processing.
How do you know if the data is big data? First of all, it is necessary to pay attention to the properties of information. Big data is characterized by:
- Volume (about 1 Petabyte);
- Velocity (possibility of regular updates);
- Variety (data is not structured or has heterogeneous formats).
Also, Variability (variability) is often added to the listed factors – data bursts that require the use of specific technologies for processing. You also need to take into account Value – the various complexity of information. Let’s give an example. The data of users of social networks and transactions carried out in the banking system have different levels of complexity.
How Big Data is collected
You can collect big data from such sources: the Internet, corporate data, devices that collect information (“smart speakers”, etc.). The data collection process is called data mining and is carried out using the following services:
- Power BI;
Information is collected in the formats text, Excel tables, SAS. During the search, the system finds Petabytes of information, which is further processed using intelligent analysis methods that reveal patterns. These include:
- neural networks;
- algorithms for detecting associative links;
- clustering algorithms;
- some of the machine learning methods.
How does big data processing look like in practice? Let’s look at the process step by step:
- The analytic program receives the task.
- The system collects the necessary information, deletes irrelevant information, and also performs decoding.
- A model or analysis algorithm is selected.
- Using the selected algorithm, the program analyzes the found patterns.
How Big Data is stored
Storing large amounts of data most often occurs in the data lake. At the same time, they are stored in different formats and degrees of structuredness:
- Structural – rows and columns from the database.
- Unstructured – documents, mail messages.
- Semi-structured – CSV, XML, JSON files.
- Binary – video, audio messages, images.
How to store large amounts of data? For this, various tools are used, first of all – Hadoop. It is a data management platform containing multiple clusters. It is used to process, store, and analyze large amounts of data, such as internet traffic data, messages and images on social networks.
Also, big data storage is often associated with other tools:
- HPPC (DAS). A supercomputer developed by LexisNexis Risk Solutions. Capable of processing data in batch mode and in real time.
- Storm. A framework developed in Clojure. Designed for processing information in real time.
Considering the issue of big data storage systems, we once again focus on the data lake. It is not exclusively a repository, as it may include a software platform. First of all, we are talking about means of integration with sources and consumers of information, clusters of storage servers.
Data lake stores large amounts of information, which are sent from there to sandboxes (data mining areas). At this stage, scenarios are developed to solve specific business problems. Note that processing big data will require huge computing power, therefore, it is advisable to use network storage. This is the best option for storing large amounts of information. Let’s list its most important advantages:
- The ability to store huge data.
- Cost effective for businesses with rapidly growing workloads or companies where various hypotheses are regularly tested.
How Big Data is used
Above, we examined how and where to store large amounts of data. Now let’s talk about the features of working with big data. After receiving and saving the data, they must be analyzed and compiled into graphs, tables, ready-made algorithms that will be understandable to the client.
In this case, it is necessary:
- Process the entire data array.
- Find correlations throughout the data set.
- Process and analyze all the information received in real time.
In connection with the above, special technologies and methods of working with big data are used. Let’s consider them in more detail. The most popular technologies include:
- MapReduce is a parallel computing framework that handles indefinitely structured data.
- NoSQL – Solves scalability and availability issues.
- Hadoop – serves for the development and execution of distributed programs running on clusters of hundreds and thousands of nodes.
There are a lot of methods and tools for working with big data. These include mining, machine learning, predictive analytics, visualization, and simulation. There are a lot of methods as of today:
- digital signal processing;
- predictive analytics;
- simulation modeling;
- spatial and statistical analysis;
- visualization of analytical data.
Working with big data also involves human participation. A Data Engineer, is a specialist who prepares the infrastructure for further work. He tests, develops and maintains databases and media systems. Also, one of the main tasks of a Data Engineer is to create a data processing pipeline.
Big Data necessarily works with Data Scientist, who creates and trains predictive models using neural networks and machine learning algorithms. It is he who helps the business find hidden patterns, predict the development of events, and optimize processes. Having got an idea of how to work with big data, where it is used, let’s look at it now.
Where Big Data is used
Where and how to use big data? The main principle of application is to quickly provide the user with information about objects, phenomena, events. Therefore, machines are able to build variable models and track results. This is primarily useful for commercial companies, such as banks.
It is the use of big data that helps prevent fraud, as well as optimize risk management. Big data is often used for scoring aimed at establishing the fact of a borrower’s trustworthiness or unreliability.
Thus, banks can effectively resist fraudulent schemes thanks to big data. Where is big data used in the banking sector? With its help you can:
- identify customer needs;
- reduce the risk of loan default;
- predict queues in branches;
- manage staff.
Speaking about big data, how to use it effectively in business, let’s consider. First of all, the choice of a business development strategy is based on the results of information analysis. Therefore, big data will help process huge amounts of data and identify which products will be in demand in the market, how to increase loyalty of regular customers and attract new ones.
Let’s take a look at big data use on the example of Netflix, which has a multimillion audience. In his work, he draws on the user experience of viewers and information from social networks, offering relevant content.
To optimize Netflix uses: browsing history, user’s search queries, information about pauses, rewinds, repeated views. When the House of Cards series was launched, based on the analysis, they ordered not a pilot, but two full seasons, and they were not mistaken! The series about political intrigue in the White House delighted the audience.
Where else is big data used? In marketing, of course! Through data analysis, marketers identify customer needs and test new ways to increase customer loyalty. Services (software) for big data can successfully solve many problems:
- RTB is suitable for setting up retargeting in order to advertise products and services only to the target audience.
- Crossss, Alytics, 1C-Bitrix BigData are irreplaceable assistants for end-to-end analytics. Their competent use will help to increase the average check, increase the personalization of ads and increase the conversion of offers.
The outlook for Big Data today is impressive. With the help of big data, you can recognize fraud, design and run effective advertising campaigns. The development of Big data contributes to the deep implementation of artificial intelligence, as well as the transition to cloud services and platforms for independent work.
By the way, you can order a Big Data server and network data storage rental from Unihost on the most favorable terms. In order to contact a specialist, use the chat on the site. We invite you to cooperate that will help your business flourish!