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The Difference Between Business Intelligence and Big Data

Business intelligence and Big Data
Matthew Hayhow

By Matthew Hayhow Web Journalist, Updated 17 May 2017

If you know anything about technology, you will have probably heard the term ‘Big Data’. As the storage capabilities of data platforms improves, so do the opportunities to uncover valuable information that can be gleaned from data. However, Big Data is often confused with Business Intelligence, and discussions of Big Data regularly conflate the two. There is a difference between Business Intelligence and Big Data, and one you should probably know, as being able to analyse large amounts of data is fast becoming a necessity that, when done resourcefully, can seriously benefit your organisation.

What's The Difference between Business Intelligence and Big Data?

A guide to how business intelligence and big data are related.

Big Data refers to data sets too large to be processed by traditional data processing applications, and should be distinguished from data that can be managed with a toolset such as Microsoft Excel. The IT research company Gartner defined Big Data as encompassing three ‘V’s:

• Volume

This is the quantity of data a business produces or wants to analyse. Put simply, there has to be a huge amount of data, hence ‘big’ data. The data is naturally too big to be handled by traditional data processing applications.

• Variety

This refers to the diversity of data sources and the collection of data itself. Big Data typically comes from a wide variety of data sources, and the data itself is varied, comprising both structured and unstructured data such as emails, videos and social media.

• Velocity

This is the speed at which data flows in from sources such as networks, business processes and social media. The flow of Big Data is characteristically immense and constant.

Big Data is important because within it is the power to advance your business by making better decisions, improving processes, extending customer engagement, preventing illicit operations and finding and profiting from new sources of revenue. Market trends, behaviours and factors which influence different actions and buying patterns can be explored, which can be used to improve your business efficiency by identifying when your target market is most active and what influences their decision making.

However, you should remember that big data is just that, data, and so not all of it will be valuable, and is useless unless it’s analysed properly.

Business Intelligence

Whilst Big Data refers to an entity, Business Intelligence (BI) is a process; it’s what you do with Big Data. Through technology, BI engages with data, whether normal or big, and extracts useful information from it. This can involve an assortment of tools, applications and methodologies that allow the collection of data from internal systems and external sources, organise it for analysis, develop and run queries against the data, and create reports and visualisations to present the results in an easy to understand manner.

Who Uses Big Data?

Big Data has ramifications for virtually every industry:

• Big Data for Retail

It is essential for retailers to know how to market to customers, handle transactions, and implement strategies to improve revenue, all of which is reliant on the interpretation of Big Data. The Glasgow-based lingerie company Ultimo managed to dramatically increase sales by analysing data pertaining to weather against data on customer buying patterns. This led to insights into customer behaviour, around which Ultimo modified its business processes. As a result, their sales increased by around 12-22%. Big Data can also drive traffic towards websites, an outcome that’s vital due to the digital nature of modern business. EasyJet’s ‘True Clarity’ campaign uses internet users’ data to target them with relevant online advertising, which helped EasyJet fill up to two planes per minute during their January sales.

• Big Data for Manufacturing 

Insight gleaned from Big Data can enhance the output of a manufacturer and improve their products whilst minimising waste. As the manufacturing industry becomes more based on analytics, businesses can solve problems faster and make more lucid business decisions.

• Big Data for Healthcare 

Big data is not just useful for sectors that want to turn as high a profit as possible. Every aspect of health care needs to be as fast and accurate as it can, which involves handling a huge amount of data. When this data is efficiently managed, health care providers can discover insights that advance patient care.

• Big Data for Government 

Analysing big data can significantly improve the management of utilities and agencies, and dealing with tasks such as reducing crime or traffic congestion. However, the government has a major responsibility to maintain transparency and privacy when handling other people’s data.

• Big Data for Education 

The analysis of big data can show the progress of students, including which students are doing and well and which are at-risk. This can lead to a better system for the assessment and support of teachers and staff.

• Big Data for Couriers 

Delivery companies can have a lot of components which need to be managed, which can be done through the storage and analysis of data. The resulting information can help a delivery company be more efficient in its processes, saving time and money. UPS stores vast amounts of data, a large portion of which comes from sensors in its vehicle. The data revealed the company’s daily performance, which prompted the creation of ORION software. This resulted in a major redesign of its drivers’ route structures. ORION used online map data to reconfigure a driver’s pickups and drop-offs in real time. The software saved UPS over 8.4 million gallons of fuel by reducing 85 million miles off daily routes. Such small improvements can lead to significant financial savings; the reduction of one daily mile for each driver saves UPS $30 million.

Implementing big data analytics software such as business intelligence can provide valuable insights and improve the operations of your business. However, there is still the matter of selecting a solution. There is so much big data analytics software available that is suited to businesses of a variety of industries, sizes and structures. Finding the right solution can take substantial time and money, not to mention creating anxiety that the solution you choose isn’t the optimum one.

With a simple phone call, you can find the right big data software with Software Advisory Service. We offer expert, non-chargeable buying advice to help find the right system for you, and can provide a shortlist of potential software vendors depending on your specific requirements. Just complete your details here so that we can find the solution you need today!

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