The difference between Big Data and Data Analytics

Those who don’t work with the technology on a daily basis may easily get confused about Big Data and Data Analytics. Still, those terms are quite important, especially for medium sized companies and large enterprises which deal with huge amounts of data of various kinds every day. If you work with data, you should have at least a general idea of Big Data and Analytics.

Big Data refers to the immense volume of data that is produced and collected by businesses all the time. Data Analytics, on the other hand, is a process performed on collected data in order to gain useful information to improve a company’s efficiency. Want to learn more? 

It’s all connected to data science

Data is everywhere. We leave it behind like a breadcrumb trail – we make transactions – data is produced; we surf on the Internet and use applications – again we leave some information about our preferences, interests and activity. 

Data science is a complex field (if you need some help come by our Data Science Services page). To put it simply, we can say that it’s goal is to extract important information and knowledge from data. Data science incorporates mathematics, statistics, computer science and programming, statistical modelling, database technologies, data modelling, artificial intelligence, natural language processing, visualization, and analytics. It is a very broad term.

Why should you be concerned about those terms?

Businesses receive customers data all the time. Some of it is of low value, incomplete or requires fixing (data cleaning) before use. Other information may be crucial for your company in order to simply operate. In most cases collected data is raw, which does not give business any additional value.  You need to use the proper technologies and techniques to deal with such type of information.Thanks to Big Data and Data Analytics we can provide crucial information for your company in order to simply operate and be competitive on the market. Businesses use a lot of data that is called “sensitive” – this is, for example, personal information about customers that nobody else should have access to.

What is Big Data?

Big Data refers to huge amounts of both unstructured and structured data that requires specific tools in order to be effectively processed. The data is collected through multiple channels – from mobile devices, the Internet, social media, industrial devices and many other sources – and stored in different formats. Think of Big Data a little bit like a huge library. It holds the answers to many of your questions, though it is not so easy to find them. Big Data deals with large amounts of data, which is impossible to handle with traditional databases or data warehouses systems.

But how much data makes it Big Data? In order to quantify what is Big Data and what isn’t, the IT industry came up with the “V’s” of  Big Data. Here it gets tricky, because some authors write about 3 V’s of Big Data, others about 5 V’s for Big Data, and if you put into Google the phrase “V’s of Big Data” yourself, you’ll see that some articles mention even 7 to 10 V’s. There are three basic ones:

• Volume – the amount of data from different sources is immense.
• Variety – Big Data consists of various types of data (structured and unstructured).
• Velocity – this is about the speed of generating, collecting and using the data.

Why is Big Data important?

Companies which use Big Data are becoming more competitive than others. Collected information can be used to:

• Optimize various processes within a company.
• Improve common operations. 
• Provide better customer service. 
• Plan personalized marketing campaigns.
• Reduce the overall cost of running the business and find new ways to increase profits.
• Make decisions faster.
• Become competitive on the market.

Those are only a few examples. Big Data is important when it comes to ensuring the security of the company and preventing fraud. All economic sectors can leverage it to work more efficiently. To benefit from Big Data, you need to know how to utilize it and what kind of technologies to use to manage information.

What is Data Analytics, and how can it be applied?

One way to take advantage of your data is analysing it to find solutions that will help you to improve your company and reduce unnecessary costs. Data analytics is about examining raw data in order to create useful insights (for business or science). How does it work? Special processes and algorithms are applied in order to find patterns, correlations between many sets of data, to formulate feedback for the business user. The main goal of data analytics for business is to enable organisations to make better, more data-driven decisions.

Why is Data Analytics important?

Big Data Analytics can provide you with many useful business insights for all departments in your company to help them work more efficiently. Reduce costs here, optimize processes there, find some new groups of potential customers – soon you’ll realize that by using data analytics you have significantly increased your company’s profits. 

Using cloud-based analytic techniques or technologies such as Hadoop, you can reduce the costs of managing data, find new ways for your organisation to grow but also improve safety of your company’s resources. This is very important for your infrastructural security – using data analytics you can efficiently monitor activity in your systems to spot suspicious activity. Thanks to data analytics you’ll be able to react faster and better to eventual cyberattacks. 

Making data-driven decisions can improve efficiency of processes performed in various departments in your company. Data analytics helps companies around the world to improve and invent new services and products by analysing customers’ needs and satisfaction, but also to automate and optimize internal processes.

How are they different?

The main difference lies in the nature of Big Data and Data Analytics. Big Data is a big amount of information of various types coming from different sources. It may seem chaotic – often without the structure and in different formats. Data Analytics is a process of analysing this data in order to reveal patterns and meaning that is almost impossible for a human to find in such a large amount of data. 

Big Data’s most important concern is storing large amounts of data. Data Analytics, on the other hand, is about using those data in order to gain business insights. Processing such amounts of data is not simple. There is a need for a lot of filtering, cleaning and transformations in order to learn something from the data. Analysing both structured and unstructured data has big business potential. High quality of data is crucial for gaining useful results of analytics. 

There are different tools to deal with Big Data and perform data analytics. Big Data requires complex solutions, which provide parallel computing, scalability, performance, availability or fault-tolerance to manage huge amounts of data – data analytics uses predictive and statistical analysis with easier tools. 

Big Data Analytics – how can you benefit from it?

All companies collect, store and process data. Today, Big Data Analytics has huge potential. It can be used to ensure the security of systems and organisation resources, reduce costs of many processes, find more ways to expand and improve services or internal process efficiency. It feels important to point out that Data Analytics and Big Data actually are strongly connected. Big Data Analytics is, after all, about analysing huge amounts of data in order to provide useful business insights to the company. Without powerful tools to store large datasets (Big Data), there would be no data analytics and without it, company development would be impossible. 

Marketing

Targeting marketing campaigns is not easy, even for small companies. Big Data and Data analytics can be used not only to  measure the effectiveness of marketing campaigns but also for their optimization. Medium sized organisations and large enterprises require big data analytics in order to personalize content, adjust marketing information to the specific customer profile and to target ads properly. 

Prospecting Customers

With Big Data Analytics you can produce complex reports about activity on your website or application, learn more about your customers and their behaviour and even find out what other groups of people might become your customers and how to approach them. 

Risk management

As your company grows, there are more potential risks. Big data analytics can help you spot the weaknesses of your organisation and eliminate them. With the right tools and techniques you’ll be able to foresee the future, identifying potential risks and mitigating them or plan how to deal with them if they occur. Big data allows business to be more client-focused. By collecting a large amount of data, companies are able to understand how products can be improved and what functionalities are needed from a customer perspective. They can track client feedback and based on these data adjust product strategies. Big Data also makes companies operate more efficiently. Analysed data can bring additional information to the business, which can produce decisions faster  and stay competitive on the market.

Make use of the data your company collects every day. Experienced IT consultants can analyse your company’s needs and suggest the best solutions to help you gain a competitive advantage. There are different technologies and techniques that can be used to collect data and process them for the business purposes. Choice of the solutions depends on what you need. Before picking software to play with Big Data, we encourage you to consult your needs with our Big Data experts. We can analyze your business case and suggest best solution and technologies, which will fit you and be most cost-effective for your business

Check out our blog for more details on Data Science and Advance Analytics:

• What is cyberscurity?
• What is an image segmentation?
• Types of analytics and how to implement them?