Big Data: optimised analysis and systems for business analysis
Big Data analysis examines large amounts of data to uncover hidden patterns, correlations, and other insights.
With today’s technology it is possible to analyze data almost immediately, with better timeframes than the slower and less efficient ones obtained using more traditional business intelligence solutions.
The concept of Big Data has existed for years; and today most organizations have understood that, by acquiring all the data they transmit in their companies, they can apply an analysis and derive a significant value from it.
But even in the 1950s, decades before anyone pronounced the term "Big Data," companies used basic analysis (essentially numbers in a spreadsheet that were processed manually) to discover insights and trends.
The new advantages that Big Data analytics brings to the table, however, are speed and efficiency. While a few years ago a company would collect data, perform analysis and discover information that could only be used for future decisions, today it can identify data and trends for immediate decisions. The ability to work faster in a smart way gives organisations a competitive edge they have never had before.
Why is Big Data analysis important?
Big Data analysis helps organizations to exploit their data and use it to identify new opportunities. This in turn leads to smarter business strategies, more effective operations, greater profits and happier customers.
The main pros of using Big Data in companies are the following:
• Cost reduction: Big Data technologies such as cloud-based analysis offer significant cost benefits when it comes to storing large amounts of data, as well as identifying more efficient ways to do business.
• Faster and more efficient decision-making: thanks to the speed of in-memory analysis combined with the ability to analyze new data sources, companies are able to view information immediately and make decisions based on what they have learned.
• New products and services: with the ability to assess customer needs and satisfaction through analysis, it also results in the possibility to offer customers what they want. Thanks to Big Data, more and more companies are creating new products to meet customers' needs.
How Big Data works: key technologies
There are more technologies that include the analysis of Big Data; let’s see now the main:
• machine learning: is a specific subset of AI, which has as its objective the formation of a machine, allows you to quickly and automatically produce models that can analyze larger and more complex data and provide faster and more accurate results, even on a very large scale.
And by building accurate models, an organization has greater possibilities to identify profitable opportunities or to avoid unknown risks.
• Data management: data must be of high quality and well selected before it can be reliably analysed. If we consider the large amount of information that flows constantly in and out of an organization, it is important to establish repeatable processes to build and maintain standards for their quality. Once the data is reliable, organisations can establish a management plan for the data that brings each part of the enterprise to the same level.
• Data Extraction: Data mining technology allows you to examine large amounts of data to discover certain models, and this information can then be used for further analysis in order to answer complex business questions. With data mining software, you can sift through the chaotic and repetitive flow of data, identifying what is relevant and use that information to evaluate probable results, thereby accelerating decision-making time.
• Memory analysis: by analyzing the data from the system memory (instead of the hard disk drive), you can extract immediate information and act on it quickly. This technology is able to remove data preparation and analytic processing latencies to test new scenarios and create models. It is not only an easy way for organizations to stay agile and make better business decisions, but it also allows you to run iterative and interactive analysis scenarios.
• Predictive analysis: Predictive analysis technology uses data, statistical algorithms and machine learning techniques to identify the probability of future results based on historical data. It is a question of providing a better assessment of what will happen in the future, so that organisations can feel more confident about making the best business decision possible. Some of the most common predictive analysis applications include fraud detection, risk assessment and the creation of marketing projects.
• Text extraction: With text mining technology, you can analyze text data from the Web as fields of comments, books and other text-based sources to discover insights never noticed before. Text mining uses machine learning or natural language processing technology to explore documents (e-mail, blogs, Twitter feeds, surveys, competition information and more) to help analyze large amounts of information and discover new topics.
Accurate and efficient analysis thanks to Techmakers
The technologies that implement Big Data are just some of the ones that make up the industry 4.0, which includes all the ideal solutions to keep companies always up to date with the latest innovations.
Techmakers is a company of professionals that has been operating for years in the industry 4.0 to offer every company technological solutions of great effectiveness, from data analysis to smart management of production and warehouse.
Thanks to Techmakers you can allow your company to enter the world of technological innovations such as Artificial Intelligence, Big Data, analytics and Internet of things, allowing you to always get the most out of your data and production.
