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26 (121) 2016
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Digitisation

Big Data – hype or reality?

by Rafał Cegielski, partner, Reewise
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Big Data – and how it will impact the digital world – is one of the key topics in the world of business and IT nowadays.  Everyone seems to be talking about it, but what really is big data really? Where is it coming from, how is it being processed, and how are the results being used?

Let’s start with the characteristics of data and its sources. The traditional source is structured data – data with a high level of organisation, such as information in a database. Information based on structured data is highly predictable and is used in companies in all kinds of IT systems – enterprise resource planning (ERP), customer relationship management (CRM), business intelligence etc.

As the level of online customer interactions is rapidly growing every year, the corresponding volume of structured data is expanding accordingly. Each e-commerce transaction or customer inquiry brings additional data to be processed – for example – the date and hour of transaction, customer  details, order or enquiry specification etc. All this structured data has to be handled by the appropriate IT systems.
 
Yet since the beginning of the new millennium,  a new type of data has become much more significant. Unstructured data which covers everything from social media posts and sensor data to emails, images and blogs is growing exponentially. According to IT market research firm International Data Corporation, unstructured data will grow to 40 zettabytes [1ZB = 1 trillion gigabytes] by 2020, resulting in a 50-fold growth from the beginning of 2010. Let’s focus on just a few examples based on a one-minute snapshot from the internet (based on research by IT consultant Excelacom made this year):

  • 701,389 logins on Facebook

  • 69,444 hours watched on Netflix

  • 150 million emails sent

  • 1,389 Uber rides

  • 527,760 photos shared on Snapchat

  • 51,000 app downloads on Apple’s App Store

  • $203,596 in sales on Amazon.com

  • 120+ new LinkedIn accounts

  • 347,222 tweets on Twitter

  • 28,194 new posts to Instagram

  • 38,052 hours of music listened to on Spotify

  • 2.4 million search queries on Google

  • 2.78 million video views on YouTube

  • 20.8 million messages on WhatsApp

The variety of the examples of unstructured data presented above and the sheer volume of information is one of the reasons why the companies are focusing on the ability to process and interpret this data more than ever before.

Processing and analysing big data is much more complicated for unstructured than for structured data. For example, a simple post on a social media portal has many elements embedded in it — the date and time it was posted, the contents  containing text and digital images, links, etc.

To make it even more complicated, unstructured data has to be matched with increasing volume of data strictly related to online transactions. Organisations require solutions that have capabilities to deal with the growing volume of information, its accelerating velocity and expanding variety – in other words – big data.

Requirements for utilisation of big data solutions are coming from public and private sectors. Some examples of implemented solutions are as follows:

  • Healthcare. Big data analytics is helping healthcare institutions by providing personalised medicine and prescriptive analytics as well as automation of patient-data reporting.  Expansion of wearable technologies and related volume of data will require adoption of new tools for its processing and analysis.

  • Manufacturing. Using big data gives an ability to predict maintenance needs and manage inconsistent component performance and availability.

  • E-commerce. Handling millions of customer transactions every hour enables retailers to offer products and services tailored to changing customer needs.

  • Banking. As the growing volume of credit-card transactions increases the risk of fraud, big data solutions enable assessment and qualification of millions of transactions as possible fraud in less than one second.

  • Retail. Text mining solutions provide the ability to analyse the context of opinions, blogs and articles posted in the web sphere and provide feedback on products or services to their providers.

  • Science. The Large Hadron Collider experiments represent about 150 million sensors delivering data 40 million times per second. Big data solutions provide analysis and qualification of collisions that can be of interest by scientists in each second.

  • Internet of Things. The exchange of large volumes of data coming from sensors of multiple devices requires a common framework for analysis and management of them.  

These examples are just a fraction of ways that big data can be used in the commercial and public sphere. In Poland, organisations are implementing big data solutions to better understand customer requirements. They are tailoring their offerings to the needs of different market segments, fraud detection and many others.  As the new directions of technology emerge and the level of innovation expands, the current ways of big data solutions utilisation seem to be just the beginning of an extremely exciting journey.

Rafal W. Cegielski (Partner, ReeWise)

ReeWise is a professional services firm focused on innovative business intelligence and big data solutions. ReeWise provides tools and services in areas of customer analytics, text mining and social media/contact channels analytics, financial analytics, risk and fraud management, technology support, advisory and architecture design. We cooperate with telecoms, financial institutions, retailers and utilities in Poland and CEE (www.reewise.com).

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