The term big data is increasingly used almost everywhere on the planet – online and offline. And it’s not just about computers. It falls under a general term called information technology, which is now part of almost all other technologies and fields of study and businesses. Big Data is not a big deal. The hype surrounding it is definitely big enough to confuse you. This article takes a look at what Big Data is. It also contains an example of how NetFlix used its data, or rather, Big Data, to better meet the needs of its customers.
What is Big Data
Until yesterday, the data stored on your company’s servers was only sorted and archived data. Suddenly Big Data slang became popular, and now your business data is Big Data. The term covers every piece of data your organization has stored so far. This includes data stored in clouds and even URLs you’ve bookmarked. Your company may not have digitized all data. You may not have structured all the data already. But then, all digital, paper, structured and unstructured data with your business is now Big Data.
In short, all data – categorized or not – present in your servers is collectively called BIG DATA. All of this data can be used to get different results using different types of analysis. Not all analyzes need to use all data. Different analyzes use different parts of BIG DATA to produce the necessary results and predictions.
Big Data is basically the data you analyze to get results that you can use for predictions and other uses. When you use the term Big Data, suddenly your business or organization is working with high-level information technology to derive different kinds of results using the same data that you have intentionally or unintentionally stored over the years.
How Big is Big Data
Essentially, all data combined is Big Data, but many researchers agree that Big Data – as such – cannot be manipulated using normal spreadsheets and regular data mining tools. data base management. They need special analysis tools like Hadoop (we’ll look at that in a separate article) so that all the data can be analyzed at once (may include analysis iterations).
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Contrary to the above, although I am not an expert on the subject, I would say that any organization’s data – large or small, organized or unorganized – is big data for that organization and the organization can choose its own tools to analyze the data.
Normally, to analyze the data, people used to create different sets of data based on one or more common fields so that the analysis becomes easy. In the case of Big Data, it is not necessary to create subsets to analyze it. We now have tools that can analyze data of any size. Presumably, these tools themselves categorize the data even as they analyze it.
I find it important to quote two sentences from the book “Big Data” by Jimmy Guterman:
” BigData: when size and performance requirements for data management become important design and decision factors for implementing a data management and analytics system.
“For some organizations, dealing with hundreds of gigabytes of data for the first time can trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes an important consideration.
So you see that volume and analytics are an important part of big data.
Big data concepts
This is another point on which most people disagree. Some experts say Big Data Concepts are three Vs:
- The variety
Others add a few more Vs to the concept:
- Veracity (Reliability)
- Variability and
I will cover Big Data concepts in a separate article because this article is already becoming important. In my opinion, the first three Vs are enough to explain the concept of Big Data.
Big Data Example – How NetFlix Used It To Solve Their Problems
Around 2008, there was an outage at NetFlix due to which many customers were left in the dark. While some could still access streaming services, most could not. Some customers have been successful in getting their DVDs rented while others have failed. A blog post on the Wall Street Journal indicates that Netflix had just started on-demand streaming.
The outage made the management think about possible future problems and therefore; he turned to Big Data. It analyzed high traffic areas, hotspots and network throughput, etc. using this data and worked on it to reduce downtime if a future issue arose as it went global. Here is the link on the Wall Street Journal blog, if you want to check out the Big Data examples.
The above summarizes what Big Data is in layman’s language. You can call it a very basic introduction. I plan to write a few more articles on related factors like – Concepts, Analysis, Big Data Tools and Uses, 3V Big Data, etc. In the meantime, if you want to add anything to the above, please comment and share with us.