What is big data?
Big data is a term used by industry professionals to describe data sets that are massive in terms of size, velocity, and complexity for traditional data management tools to handle.
As the Internet becomes more commonplace, businesses are interacting with and generating more data than ever before. Large tech companies handle absolutely staggering amounts of data. Walmart processes over 1 million transactions each day in the United States alone, and Google users make over 100 billion searches per day. The quantity of data in the world is expected to double every 2 years moving forward. That's a lot of data! At such a scale, even the most robust BI tool will struggle to keep up.
At data centers like this one, Amazon, Google, and other tech companies store and analyze their user data.
It’s not just the largest tech companies dealing with big data issues, though. Even small organizations are collecting more data than they know what to do with. As more business processes move online, the amount of data available to an organization keeps going up. Businesses may end up needing a big data solution even if they don't intend to collect that much information.
How can I tell if my data is big data?
There are three main criteria that set big data apart from its smaller, less complicated counterpart. These criteria are often called the ‘three v’s.’
Volume. Big data sets are informationally larger than regular data sets. A good rule of thumb is that if the data set is large enough that simply storing it causes logistical problems, it’s big data. There’s no clear cutoff that separates the two; it’s all relational compared to the scale of data your business generally collects.
Some big data sets are just a few terabytes, while others can be multiple petabytes. The largest data sets, collected by the largest multinational businesses, can be exponentially bigger than that.
Variety. Big data sets contain more types of data than regular data sets. A regular data set usually only collects one or two kinds of data. These can usually be stored easily as an integer or a still image. These statistics can be compared easily to other data sets in some kind of relational database.
Big data often includes unstructured and semi-structured data types like text, audio, and video. This data can rarely be stored as a simple integer or image, and needs more work done to transform it into something usable. Traditional data processing tools are often poorly equipped to process these more complex data types.
Velocity. Big data sets grow much faster than regular data sets. Big data is produced more continually, and more data is collected at once. Because of this, snapshots of big data become outdated much faster than smaller, slower data sets. New technologies such as IoT
The velocity of big data also refers to how fast it needs to be processed. Because big data becomes outdated quickly, those collecting big data must process it in as close to real time as possible.
What are the benefits of big data?
Big data allows businesses to analyze and respond to data in ways that would be impossible using smaller data sets. The volume, variety, and velocity of the data collected makes big data an essential tool for any organization trying to improve.
Big data allows for a more complete picture. Some trends can’t be isolated without analyzing massive amounts of information. What may look like a flat, consistent trend in a smaller data set could have a slight positive or negative trend when viewed as part of a big data set.
Some of these trends may be very minor, but at the scale that large enterprises operate, even a trend of a few fractions of a percentage point can represent millions of dollars of lost revenue. In today’s hypercompetitive markets, even the smallest margin can help edge out the competition.
Enterprise-scale solutions like Dundas BI are ideal for big data applications.
Big data allows for stronger predictive analysis. Using big data, analysts can refine and improve their predictive models for future business strategies. Retail businesses can collect sales data and use it to inform revenue predictions for later quarters. Organizations with a large physical plant can better predict when maintenance needs to happen and when equipment should be replaced.
Big data can improve customer relationships. R&D departments can use customer trends to drive the creation of new products and solve common problems with current ones. By looking at large amounts of sales data, with the ability to refine it in dozens of different ways, companies can discover market niches that would have been invisible with traditional data solutions.
Advertising, especially online advertising, has been revolutionized by the advent of big data. Now, sellers can personalize ads down to the smallest degree, only showing them to the people most likely to click on them. This personalization is only possible due to the massive data sets of user information compiled by the largest tech companies.
Big data makes machine learning possible. Machine learning on the scale it’s being used at today is only possible thanks to big data. The algorithms that drive machine learning need massive data sets of information to use as a starting point. Without big data to train them on, these learning models would be built on incomplete information and spit out incorrect results.
Can I use regular BI tools for big data solutions?
Most BI tools will have no problem handling big data. Cloud-based solutions don’t require investment in the powerful hardware that traditional on-premise software needs for its calculations. Storage is also much easier, though many BI tools require additional fees for extra storage.
Large companies should ensure that a BI tool can operate at enterprise scale before investing. Some BI tools are a better fit for smaller companies with less moving parts, while others offer a robust set of tools that only larger companies will be able to make use of.
Big data solutions like Looker (pictured above) are robust, but can be complex.
Collecting and analyzing big data is quickly changing from something that only the largest, most technically advanced companies do into an everyday task that even the smallest shops should devote resources to. Talk with our team of experts to find the tool that’s right for your organization so that you can stay ahead of the curve and crush the competition.
