We are dreadfully sorry, but you appear to be using a rather out of date browser…
There's nothing wrong with that but our site was built to take advantage of the latest HTML & CSS features.
If you want to look at updating to a newer browser you can visit this site to get an idea of the options you have: https://whatbrowser.org/
Data Analytics is the process whereby sets of data are examined to allow conclusions to be made, based on the information they contain. Many data analytics techniques have been automated into algorithms and mechanical processes- that allow raw data to be transformed into data understood by humans. Data analytics reveals metrics and trends that otherwise would not be understood from large amounts of data.
Data analysis technologies are widely used across most industries, to allow organisations to make more strategic business decisions. Data analytics can help businesses increase their revenues, improve their efficiency, improve customer service efforts and optimise their marketing campaigns. Data analytics also helps businesses to respond quicker to emerging trends within the industry and can also help them gain a competitive edge over their rivals.
Big Data Analytics
The concept of big data has been around for many years, with most organisations understanding that if they capture all the data that is associated with their business, they can apply analytics and gain some valuable insight from it.
The process of obtaining data has changed significantly over the years. Now more than ever, speed and efficiency are key benefits that make the process smoother for organisations. With the ability to identify insights for immediate decisions, big data analytics provides businesses with the ability to work faster and stay agile.
Why is Data Analytics Important?
- Data allows organisations to harness their data and use it to identify new opportunities.
- Data analytics is key in helping businesses optimise their performance.
- Research into big data in companies found that data analytics provided value to companies in the following ways:
Types of Data Analytics
1) Descriptive Analytics
2) Diagnostic Analytics
3) Predictive Analytics
4) Prescriptive Analytics
With several types of data analytics, businesses have a broader scope of options when it comes to determining how deep they need to dive in to data analysis and understanding what suits their business best. Currents trends indicate that more and more businesses enter a situation where they require advanced data analysis and so by utilising it, they can help to make better decisions on behalf of the business.
Younger generations are accumulating more spending power, a presence in the job market cemented. The travel and tourism industry could see a period of transition where rapid technological changes, motivations for travelling, and new marketing methods take centre stage.
Are you falling foul of focusing too much on fake KPIs? Discover what to do when your performance drops and your first instinct is to throw more traffic at the problem.
At a recent Travolution summit I was introduced to the concept of 'de-averaging' your users. It offers some useful angles to slice your data to make different decisions and improve performance. See how you could apply it.