What is Big Data?

By 17 October 2022Blog, csx-news-1

Back in 2012, Gartner highlighted the importance of Big Data. According to the tech research firm, in order to deliver true business benefits, “big data” necessitates creative processing methods for a variety of new and current data. Since then, the sphere of data processing has tremendously evolved. 

According to SAS, Big data’s relevance is not just dependent on the volume of data you have. How you use it determines its value. Any data source can be used to gather information, which can then be analysed to discover solutions that:

  • simplify resource management
  • boost operational effectiveness
  • optimise product development
  • provide new income and growth prospects
  • facilitate wise decision-making.

Benefits of Big Data 

Big data and high-performance analytics enable you to quickly identify the reasons of issues, faults, and failures, among other business-related tasks.

  • Quicker and more precisely detecting irregularities than the human eye.
  • Enhancing patient outcomes by quickly extracting knowledge from medical picture data.
  • Full risk portfolios are quickly recalculated.
  • The improvement of the classification accuracy and response time of deep learning models.
  • Spotting fraud before it has an impact on your business.

Popular Applications of Big Data

  • Weather Forecast: Weather forecasting is provided by IBM Deep Thunder, a research initiative that uses big data and high-performance computers. IBM is also helping Tokyo by providing better weather forecasts for natural disasters or by estimating the likelihood of damaged electricity lines.
  • Virtual Assistant: Big data analysis enables virtual personal assistant tools (like Siri on Apple products, Cortana on Windows computers, and Google Assistant on Android devices) to respond to a variety of questions. As an illustration, let’s say a user asks, “Do I need to bring a raincoat?” The tool would gather information such as the user’s location, the season, and the weather conditions at that location, then analyze the information to determine whether there is a chance of rain, and then respond with the appropriate information.
  •  Media and Entertainment Sector: Companies that offer media and entertainment services, such as Netflix, Amazon Prime, and Spotify, analyze the user data they acquire. To determine the next marketing strategy, data is collected and analyzed to determine the type of video, music, and length of time consumers spend on a website.
  • Education Sector: Big data is used by organizations that conduct online educational courses to find candidates who are interested in those courses. If someone searches for a YouTube tutorial video on a certain topic, an organization offering online or offline courses on that topic will subsequently send that individual an online advertisement for their course.

The seven Vs of Big Data

You want to make sure your business is gaining value from the data after addressing volume, velocity, variety, variability, truthfulness, and visualization, which requires a lot of time, effort, and resources.

Volume

Big data’s primary attribute is this. Big data is defined here as “BIG” by the term volume. We are aware that gigabytes are insufficient to store the enormous amount of data that is generated every day. As a result, data is now measured in Zettabytes, Exabytes, and Yottabytes. For instance, every minute, about 50 hours of videos are uploaded to YouTube.

Variety

Variety here refers to several kinds of data sources. Big data can be structured, semi-structured, or unstructured. Unstructured data, such as audio, video, photos, and text files, are the only kind of data that are produced in vast amounts in the modern world. Because they don’t follow any rules, these types of data are challenging to map and distinguish from important data.

Velocity

Velocity in this context refers to how quickly the data can be accessible and processed. For instance, it should be easy to access social network posts, YouTube videos, audio files, and photographs as soon as feasible.

Variability

Variety is distinct from variation. Data that is variable is constantly changing information. Understanding and correctly interpreting the meanings of raw data are primarily the focus of variability. For instance, a soda shop might have six different soda blends, but if you consistently order the same blend and it tastes different every time, it is variability. The same is true for data, and if it is constantly changing, it may have an effect on the data’s quality.

Veracity

If your data is inaccurate, it is useless, and this is where the idea of veracity comes in. It all comes down to making sure the data you collect is accurate and keeping erroneous data out of your systems. It also refers to the reliability or caliber of the data that a corporation acquires and uses to generate insightful conclusions.

Visualization

Here, visualization refers to the manner in which you might show your data to management for use in making decisions. We are all aware that data may be shown in a variety of formats, including word documents, excel spreadsheets, and visual charts. Regardless of the format, the data should be simple to read, comprehend, and access, which is why data visualization is crucial.

Value

Value is known as the end game in big data. Every user needs to understand that the organization needs some value after efforts are made and resources are spent on the above mentioned V’s. Big Data can help a user provide value if it is done and processed correctly.

Conclusion

You are almost ready to make your big data system accessible to users now that the necessary infrastructure is in place. However, as the big data environment may differ significantly from well-known database and data warehouse technologies, considerable training is necessary. Access rights, permissions, and other security and data governance requirements must also be considered. This is truly just where the big data journey begins.