Big data. You know the term. You’ve heard it countless times. Most likely, you’ve heard the phrase spoken with a negative twist.
- Big data is watching you.
- Big data knows everything about you.
- Big data isn’t your friend.
- Big data is the antithesis of privacy.
The truth of the matter is that, until the singularity occurs, big data itself isn’t capable of acting against you. Big data is actually a field of analytics that aims to extract information from data sets that are too large and complex to be managed by traditional data-processing software (let alone by a person).
Small to mid-sized businesses might keep databases of clients. Within those databases, there might be hundreds or even thousands of client and customer records that contain information like name, phone, email, address, company name, maybe an account number, and a few other bits of information. But those records tend to be limited in both size and scope.
Databases of that size are pretty easily managed with off-the-shelf hardware and software. Say, for example, your company makes use of the MySQL database. For the management of these databases, a tool like phpMyAdmin would be enough. You could easily run queries and add/delete/modify tables with ease. And a relational database (such as MySQL) is perfectly suited for your data.
Now, consider an enterprise-level company. All of a sudden those databases could be filled with hundreds of thousands or millions of customers, each with numerous fields and entries. At this point, neither the standard tools nor the relational database is up to the task. When a database grows to this level, special tools like MongoDB and Elastic are required.
That’s where Big Data comes into play. Large volumes of data, structured and unstructured, have become necessary for modern, agile businesses not just to stay ahead of their competition, but to stay afloat.
But the truth of the matter is, the most important aspect of Big Data isn’t how the data is housed and manipulated, but what they do with the data.
Big Data vs. Data Science
Let’s discern these two terms.
First, Data Science is an umbrella term that considers all techniques and tools used for the life cycle of massive data sets. Big Data, however, refers to the actual data sets Data Science works with.
To review:
- Big data – massive data sets.
- Data Science – a field that looks at ways to analyze, systematically extract information from or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing software.
Granted, that’s a very simplistic way of viewing it, but it’s an easy way to understand the difference between Big Data and Data Science.
Now that you understand the terms, let’s examine why Data Science is so important to modern businesses.
What Are Data Scientists?
In the field of data science, data scientists are the magicians that make it all happen. These specialists have advanced training in statistics, math, and computer science and have extensive training in data visualization, data mining, and information management.
In other words, data scientists can work with data in ways that the average person has never considered. These skills are incredibly important to large businesses. Why? Because with those skills, data scientists can help guide the business into the future and help deliver a bottom line that might not have been otherwise possible. On top of that, data scientists can:
- Mitigate fraud.
- Deliver relevance on an unheard-of level.
- Help to personalize the consumer experience.
Why Is Data Science So Important to Business?
Now we’ve reached the heart of the topic: Why is data science so important to business? Let’s examine some of these reasons.
Customer relations
The biggest advantage of data science is that it helps businesses understand what drives consumers and predict the trends they might follow. The importance of this can’t be overstated. Given how much competition there is within the business landscape, anything and everything a company can do to get ahead of the competition could mean the difference between success and failure.
Being able to better predict trends means you can develop new products, re-engineer current products, and make intelligent decisions on marketing. In fact, without the ability to predict trends, marketing is nothing more than guesswork. But with data science’s ability to identify patterns, companies are better prepared to market in a world where marketing means everything.
Empowering management
Data science also makes it possible for management (and other upper-tier employees) to help departments maximize their capabilities. It’s not just about marketing – it’s also about R&D, product design and production, shipping, and cost-cutting. In fact, every single department within a business can benefit from data science. But helping management to guide how the fruits of the data science labor are used can be a game-changing factor that contributes to the growth of a company.
Identifying opportunities
Tucked within those trends that data science uncovers is a wealth of opportunity. A data scientist can use big data to help your company better refine your processes to make manufacturing and production more efficient. Data science can also help your company uncover untapped markets. Thanks to data analytics and visualization, that information can even help your developers create better algorithms to supercharge your delivery pipeline.
Data science is also capable of helping you get the most out of your technology—from standard software to the cloud, the results of data analysis can drastically improve how your platforms perform.
Finding the right talent
There’s another area that data science can help your business with, one you might have not considered before: hiring the right talent. The recruiting of employees (such as developers, designers, engineers, and management) is a challenging task. Get the selection wrong and you could set your business back weeks.
The hiring practice has changed from the days of old. No more can you simply depend on a resume and interview to hire a new developer – you have to take social media, corporate databases, and job search websites into consideration. When you’re looking at hundreds (or even thousands) of possible candidates, that’s a lot of data to comb through.
Thankfully, you have data science on your side, which is perfectly capable of scraping that data and presenting it to you in a way that makes it far easier to draw the necessary conclusions about possible candidates.
Conclusion
Without data science, enterprise-level companies would find themselves challenged to not only continue to grow their business but to keep from being buried by the competition. When your business grows beyond the simple database, it’s time you consider putting Big Data and data science to work.
