How Big IT Giants Manage Problems related to Big Data

Aditya Pande
3 min readSep 17, 2020

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In today’s world , managing,maintaining and storing data has became a huge problem in today’s world.If we want to store large amount of data it will include high costs.We will see how big mnc manage and also store huge data with high speed and efficiency.

Facebook:

Arguably the world’s most popular social media network with more than two billion monthly active users worldwide, Facebook stores enormous amounts of user data, making it a massive data wonderland. It’s estimated that there will be more than 183 million Facebook users in the United States alone by October 2019. Facebook is still under the top 100 public companies in the world, with a market value of approximately $475 billion.Every day, we feed Facebook’s data beast with mounds of information. Every 60 seconds, 136,000 photos are uploaded, 510,000 comments are posted, and 293,000 status updates are posted. That is a LOT of data.

Facebook designs its own servers and networking. It designs and builds its own data centers. Its staff writes most of its own applications and creates virtually all of its own middleware. Everything about its operational IT unites it in one extremely large system that is used by internal and external folks alike.Facebook, which has a clear do-it-yourself IT approach, also designs its own servers and networking. It designs and builds its own data centres. Its staff writes most of its own applications and creates virtually all of its own middleware. Everything about its operational IT unites it in one extremely large system that is used by internal and external folks alike.

Google:

Google are probably responsible for introducing people to the benefits of analysing and interpreting Big Data in their day‐to‐day lives. Google uses the data from its Web index to initially match queries with potentially useful results. This is augmented with data from trusted sources and other sites that have been ranked for accuracy by machine‐learning algorithms designed to assess the reliability of data. Google monetized their search engine by working out how to capture the data it collects from us as we browse the Web, building up vast revenues by becoming the biggest sellers of online advertising in the world. Then they used the huge resources they were building up to rapidly expand, identifying growth areas such as mobile and Internet of Things in which to also apply their data‐driven business model.

What makes Google’s approach so different is that it’s unwilling to stop there and simply rely on past research, conventional wisdom or industry best practice. The team is looking for unique insight into how these factors predict success at Google.

Various factors/problems of Big Data

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