O que é Big Data - Conceitos básicos

Summary

In this video, Fábio from Boson Treinamentos introduces the concept of Big Data, explaining its significance and applications in today's world. He covers the basic characteristics of Big Data, such as volume, velocity, and variety, and highlights how it involves processing vast amounts of structured and unstructured data. Fábio also discusses the importance of Big Data's value, veracity, and various uses in industries like social media, healthcare, and e-commerce. He provides resources for further learning, including online courses, and concludes with the role of Big Data in shaping future technological trends.

Takeaways

• 😀 Big Data refers to the processing and analysis of extremely large data sets that cannot be handled using traditional data processing tools.
• 😀 Big Data involves data from various sources, including structured, semi-structured, and unstructured data.
• 😀 Structured data is organized and stored in traditional databases, while unstructured data includes audio, video, images, and text.
• 😀 Traditional databases like SQL Server or Oracle cannot process or store Big Data due to its massive volume and variety.
• 😀 Technologies involved in Big Data include distributed file systems, parallel processing, cloud computing, and artificial intelligence.
• 😀 Big Data is characterized by the '3Vs': Volume (amount of data), Velocity (speed of data generation), and Variety (different types of data).
• 😀 The volume of data worldwide is estimated to reach 35 zettabytes by 2020, with data doubling every two years.
• 😀 The variety of Big Data includes not only transactional data but also social media data, sensor data, and multimedia like images and videos.
• 😀 Velocity refers to how quickly data is generated and processed, with some tools unable to handle the rapid influx of information.
• 😀 Additional 'Vs' in Big Data include Veracity (trustworthiness of data) and Value (the practical benefit of analyzing Big Data).
• 😀 Big Data can create value for businesses by improving efficiency, detecting new opportunities, reducing costs, and enhancing customer satisfaction.
• 😀 Applications of Big Data include social media monitoring, financial data analysis, traffic models, and systems like Netflix's recommendation engine.
• 😀 Major companies like IBM, Google, and Microsoft are heavily involved in Big Data, and there are many online courses and resources available to learn about it.

Q & A

What is Big Data?

Big Data refers to the processing and analysis of extremely large datasets that cannot be handled using traditional data processing tools. It involves managing vast amounts of data that come from a variety of structured, semi-structured, and unstructured sources.

What are the main characteristics of Big Data?

The main characteristics of Big Data are often referred to as the 'Three Vs': Volume (the sheer amount of data), Velocity (the speed at which data is generated and processed), and Variety (the diversity of data types and sources). There are also two additional Vs: Veracity (data reliability) and Value (the usefulness of the data).

How does Big Data differ from traditional data processing?

Traditional data processing tools, such as SQL databases, are limited in handling extremely large datasets or diverse data formats. Big Data utilizes specialized technologies that can store, manage, and analyze data that is too complex or large for conventional systems.

What types of data are included in Big Data?

Big Data includes structured data (e.g., numbers and text in tables), semi-structured data (e.g., JSON, XML), and unstructured data (e.g., videos, images, audio files, social media posts, etc.). The majority of Big Data consists of unstructured data.

What is the importance of 'Volume' in Big Data?

Volume refers to the massive amounts of data generated and stored. It is estimated that by 2020, there would be 35 zettabytes (ZB) of data in the world, which is a vast scale that traditional systems cannot handle. The sheer scale of data is one of the primary features of Big Data.

Why is 'Variety' important in Big Data?

Variety is crucial because Big Data encompasses a wide range of data types, including structured, semi-structured, and unstructured data. This diversity comes from sources like social media, emails, videos, IoT sensors, and web logs, all of which need to be processed and analyzed together to gain meaningful insights.

What is meant by the 'Velocity' of data in Big Data?

Velocity refers to the speed at which data is generated and processed. In many cases, data is produced at a rapid pace, and traditional systems cannot keep up with the rate at which this data needs to be stored or analyzed. Big Data technologies are designed to handle real-time or near-real-time data streams.

How do 'Veracity' and 'Value' play a role in Big Data?

Veracity ensures that the data is reliable and consistent, which is important for accurate analysis. Value refers to the usefulness of the data; it must provide actionable insights that can lead to improved decision-making or outcomes. Without value, the data cannot justify the efforts spent on processing it.

What are some applications of Big Data?

Big Data is applied in various fields, such as social media monitoring, movie recommendation systems like Netflix, web analytics for e-commerce sites, traffic management through sensors, medical data analysis, financial fraud detection, and much more. The versatility of Big Data technologies makes them useful in almost every industry.

What are some companies involved in Big Data technologies?

Several companies are heavily involved in Big Data technologies, including IBM, Google, SAP, Teradata, Microsoft, and specialized firms like New Relic and Tableau. These companies provide tools and solutions for managing and analyzing large datasets across various sectors.