When your business grows beyond simply databases, it's time for you to consider putting Big Data and data science to work.
Big data. You know the term. You've heard this countless times. Most likely, you have heard the phrase pronounced with a negative twist.
- Big data is watching you.
- Big data knows everything about you.
- Big data is not your friend.
- Big data is the antithesis of privacy.
The truth is, until the singularity occurs, big data itself is not capable of acting against you. Big data is actually a field of analysis 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 and medium-sized businesses can maintain customer databases. Within these databases, there may be hundreds or even thousands of customer records that contain information such as name, phone number, email, address, company name, perhaps an account number, and some other information. But these registries tend to be limited in both size and scope.
Databases of this size are easily managed with off-the-shelf hardware and software. Let's say, for example, that your company makes use of the MySQL database. To manage these databases, a tool like phpMyAdmin would be enough. You can easily run queries and add/delete/modify tables with ease. And a relational database (like MySQL) is perfectly suited for your data.
Now consider an enterprise-level company. Suddenly, these databases could be filled with hundreds of thousands or millions of customers, each with multiple fields and entries. At this point, neither the standard tools nor the relational database are up to the task. When a database reaches this level, special tools like MongoDB and Elastic are required.
That's where Big Data comes in. Massive volumes of data, both structured and unstructured, have become necessary for modern, agile companies to not only stay ahead of the competition, but also stay afloat.
But the truth is that the most important aspect of Big Data is not how the data is stored and manipulated, but what they do with the data.
Big Data x Data Science
Let's discern these two terms.
First, Data Science is an umbrella term that considers all techniques and tools used for the lifecycle of massive data sets. Big Data, however, refers to the actual data sets that Data Science works with.
To review:
- Big data – massive sets of data.
- Data Science – a field that seeks ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be handled by traditional data processing software.
Granted, this is a very simplistic way of looking at things, but it is 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 for modern businesses.
What are data scientists?
In the field of data science, data scientists are the magicians who make everything happen. These experts have advanced training in statistics, mathematics 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 extremely important for large companies. Why? Because with these skills, data scientists can help guide businesses into the future and help deliver financial results that wouldn't otherwise be possible. Additionally, data scientists can:
- Mitigate fraud.
- Deliver relevance at an unprecedented level.
- Help personalize the consumer experience.
Why is data science so important for business?
Now we get to the heart of the topic: why is data science so important for business? Let's examine some of these reasons.
Customer relationship
The biggest advantage of data science is that it helps companies understand what motivates consumers and predict what trends they might follow. The importance of this cannot be overstated. Given the amount of competition that exists in the business landscape, anything and everything a company can do to stay ahead of the competition can mean the difference between success and failure.
Being able to better predict trends means you can develop new products, redesign current products, and make smart marketing decisions. 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 enables management (and other higher-level employees) to help departments maximize their capabilities. It's not just about marketing – it's also about research and development, product design and production, shipping and cost reduction. In fact, every department in a company can benefit from data science. But helping management guide how the fruits of data science labor are used can be a game-changer that contributes to a company's growth.
Identifying opportunities
Hidden within these trends that data science reveals are a wealth of opportunities. A data scientist can use big data to help your company better refine its processes to make manufacturing and production more efficient. Data science can also help your company discover untapped markets. Thanks to data analytics and visualization, this information can even help your developers create better algorithms to supercharge your delivery pipeline.
Data science can also help you make the most of your technology, from standard software to cloud the results of data analysis can dramatically improve the performance of your platforms.
Finding the right talent
There's another area where data science can help your business, one you may not have considered before: hiring the right talent. Recruiting employees (like developers , designers, engineers, and management) is a challenging task. Make the wrong selection and you could set your business back weeks.
Hiring practice has changed since ancient times. You can no longer simply rely on a resume and an interview to hire a new developer – you must consider social media, corporate databases, and job search sites. When you're looking at hundreds (or even thousands) of potential candidates, that's a lot of data to analyze.
Fortunately, you have data science on your side, which is perfectly capable of extracting this data and presenting it to you in a way that makes it much easier to draw the necessary conclusions about potential candidates.
Conclusion
Without data science, enterprise-level companies would find themselves challenged not only to continue expanding their businesses, but also to avoid being overwhelmed by competition. When your business grows beyond simply databases, it's time for you to consider putting Big Data and data science to work.
Source: BairesDev
