Big data literally just means a lot of data . These are extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Big data ‘tools’ and skilled data analytics specialists
Big data includes problems that involve large data sets that you can’t analyse individually. Big data is used in many companies to get information that can help them run their operations better or more efficiently. Such companies would typically have a lot of data to look at before reaching a conclusion. Big data analytics requires the use of big data ‘tools’ as well as skilled data analytics specialists. The two go hand in hand as you will need persons who understand the process as well as the tools to expose the secrets held within. For example a company like Facebook uses big data tools to understand more about you and provide you with a feed that you in theory should find interesting. Another example is with Credit card companies. They use data feeds to analyse millions of transactions which can be used to find patterns to known fraudulent or detect net suspicions patterns that don’t match the mode transaction pattern. Transaction speed is key to a great customer experience – nobody wants to wait longer than they need to for their favourite Café Latte, do they?
4 key elements that define big data
The implication of big data usually is that you have so much data that you can’t analyse all of the data at once, because the amount of memory it would take to hold the data in memory to process and analyse it is greater than the amount of available memory. Big data has got 4 key elements that define it, Velocity, Volume, Variety and Variability. These are the key elements that make today’s Big Data different from yesterday’s data analytics, indeed we have about 5 exabytes of data contained in the system we call the internet today. While much of that may be videos of dogs doing the funniest things, much of the 3 petabytes that crosses the internet every day contains valuable information. This is why today’s big data is different and understanding it gives you an upper hand in everyday business decisions and into the human condition itself.
Reasons why Big Data is important
More companies today than before have realised the importance of big data. The need to understand the subject for everyday and future benefits is firmly on the radar and it’s clear putting some strategies in place is the only way to manage large structured and unstructured data.
Some reasons why big data is important:
- Planning and forecasting: If we could understand what the future trend preferences are or what current trends are and how they affect decisions now and decisions tomorrow, we may do things differently now wouldn’t we? Big data gives you the opportunity to have this understanding. With the data we have today we could somewhat predict the future trends or earnings and thus the direction in which the stock price would move. This can be a boon for Investors and businesses.
- Problem Solving: Big data can be useful in solving problems that involve large data sets and solutions that require complex analysis because of the amount of data involved. This applies to problems that involve huge amounts of data. Usually because the data is too big, analyses usually have to be done on random segments of the data, which allows models to be built and to compare against other parts of the data. The results can help understand situations better hence solve any problem expected or otherwise current.
- Competitive advantage: Data is now a big factor in every organisation. Information is power, big data will become the basis of competition between individual firms as it will help in increasing productivity and efficiency, based on information known over competitors. This is an important function in the overall global economy, and is proving to be an essential factor of production. Many observers believe that big data is the new thing that will see some companies leap frog others in our shrinking, increasingly connected digital world.