Imran Zaman The founder of CALLTHEPM.COM Blog. He works as a program manager delivering digital transformation across fortune 500 companies.

Getting A Handle On Data Growth

3 min read

data-storage-growth-projections

Big data is big business, and many businesses are using it to achieve tremendous growth and a competitive advantage. Businesses now have access to enormous sets of data that can be collected from many different sources. However, it’s simply not possible to process and transform this amount of data into useful information with the standard tools that are currently available to many businesses. The challenge that businesses face is knowing how to use this information to their advantage. Let’s explore some of the solutions that are available to businesses that want to harness the power of big data.

Why the Exponential Growth in Big Data?

exponential-growth-in-big-data

The reason for exponential growth in big data is a function of growth in technology to collect it, store it and analyse it. Every day, the New York Stock Exchange generates one terabyte of new trading data. Facebook generates over 500 terabytes of new data each day from its 2.45 billion active users. This data includes messages, photos, videos and comments.

In addition, the Internet generates about 2.5 quintillion bytes of data every day. Big data analytics is expected to grow into a £106 billion industry by the end of 2023. Now, 97.2% of all organisations are investing in big data and the AI required to harness it – and with good reason. It is estimated that Netflix saves £1.2 billion a year on customer retention by correctly using big data. Big data can help businesses give customers what they need, and this means revenue growth and greater returns.

Challenges Organisations Face in Managing Big Data

Internet of Things (IoT)

All businesses can use these external data sources for strategic planning, making business decisions and improving customer service. The amount of information collected from customers that visit websites is mind-blowing. Old school customer relationship management meant convincing customers to give your business feedback and take satisfaction surveys, but this only captures a portion of the customer base. Now, it is possible to capture information about every customer who visits your website and to know how they behave when they get there. This allows you to fine-tune your product presentations and optimise your offerings to individual customer preferences, giving your users a personalised experience.

The challenge faced by businesses is knowing :

  • How to collect, store and organise the data in a way that allows them to see the big picture.
  • How will we manage and use the 40 trillion gigabytes of data that will be generated in 2020?
  • How do you know which information will be useful to your organisation?
  • How do you put this data in a form that can help drive strategic decisions and planning? There is a difference between collecting ‘just’ data and collecting useful data.

5 Ways Your Organisation Can Handle Big Data

customer-data-growth Organisations are faced with many challenges in making sense of the growing mountain of data, and this pool of data is expected to become even bigger in the future. Fortunately, there are several tools that can help your organisation get a handle on this growing amount of information so that you can use it to drive strategic decisions and make informed business decisions. Here are a few technologies that are being utilised by organisations to drive growth using big data.

1. Cloud Computing

cloud-computing

One of the biggest innovations to handle the massive scale of big data is using cloud computing as infrastructure. Cloud computing makes data management more scalable than older, stand-alone systems. The best thing about cloud computing is that it entails a relatively low investment cost. There is little, if any, hardware to install and the number of vendors in this area is growing rapidly.

2. Infrastructure as a Service (IaaS)

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Cloud providers offer Infrastructure as a Service (IAAS), and they handle any maintenance and operational tasks. Many of them offer a pay-as-you-go model, or you can choose a package that includes all the services you require. Many times, the costs of these services are miniscule in comparison to managing them in-house. You can experience the benefits of big data and cloud computing without the hassle and expense of maintaining the system.

3. Business Intelligence (BI)

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There is a difference between big data and business intelligence. Big data is just a general term for a large amount of data. On the other hand, business intelligence means collecting data from the big data pool to solve a specific problem or to generate a scenario. Business intelligence gives meaning to big data and translates it into a form that can be understood. For instance, it might be presented as infographics or ranking reports. This has developed into a specialised set of services that involves data mining, which is the ability to extract and collate the data. This is a necessary part of overcoming the challenge of making big data useful to organisations.

4. Internet of Things (IoT)

internet-of-things

The Internet of Things (IoT) refers to a network of interrelated and interconnected digital machines and devices. This network can transfer data between systems without the need for human interaction with the computer. These devices collect data using sensors and other input devices, such as video cameras. They collect and manage this data to provide real-time analytics. This sophisticated system forms its own ecosystem of information that can be tapped into for business intelligence and marketing decisions. Home automation with connected devices and wearable technology are an example of this technology in use. The devices use sensors to collect the data, which is then sent for analysis using AI. These applications are only the tip of the iceberg in this area of big-data collection and use.

5. Data Modelling

data-growth-and-data-modelling

Data modelling is another tool that businesses can use to make data-driven decisions in their organisation. Data modelling is used to create conceptual representations of different data sets and to understand the associations between them. It is used to enforce rules and regulations on the data. For instance, it might execute a set of rules for when a user attempts to log-in to an account if it has been identified as potential fraud or a potential security threat. It might be used to trigger an offer that is automatically sent to a customer who abandons their shopping cart. These are only a few examples of how data modelling can be used.

Conclusion

Big Data Solutions

Big data is the future of organisations and knowing how to manage it is the key to achieving and maintaining a competitive advantage. As you can see, there are many new tools being developed to help your organisation access and manage the growing amount of data that is now available. Big data will drive business decisions in the future, and now you have the tools required to use it to your advantage.

Imran Zaman The founder of CALLTHEPM.COM Blog. He works as a program manager delivering digital transformation across fortune 500 companies.