It's essentially exactly what it says - a really, really huge collection of information drawn from a myriad of internal and external sources. According to Gartner information becomes big data when the volume can no longer be managed with normal database tools.
One of the difficulties many airlines face is staying abreast of these disruptive technologies and establishing themselves as retail outlets for their services.
Collecting, storing and analysing big data provides operational intelligence insights that can help make a company more productive, profitable, competitive and secure.
On a practical level, it helps you better target your audience, implement personalisation strategies, speed up supply chain processes, and even change the way your run your business entirely as you open new avenues of competitive advantage.
Sources of big data are all around us and can roughly be divided into business data, human data, and machine data from the internet of things.
Typically these are: social media, archives, public web, data storage, media, sensor data (such as from cars, road cameras or cell towers, etc), web server log files, documents, apps, etc. It could be flight path information, weather changes over a decade, the number of people attending a concert, medical records or podcasts - the list is endless and growing by the minute.
IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. This infographic explains and gives examples of each.
The short answer is: yes. To stay competitive a business needs to know as much as it can about people, the environment it's operating in, and who and where the competitors are. Without it, everything is very much guess work.
Big data analytics helps businesses:
Big data future uses and applications. Graphic: grasundsterne GmbH. Source: Sap.com
Big data is not only about storing and extracting charts of information, but using the proper mining technologies to find the relevant information within each type. These include Hadoop, MapReduce, YARN, Pig, Apache, Flume, Hive, Cassandra and many more.
There are so many big data technology options and vendors, it can be difficult to find the right answer to what you need. It's no wonder data science is becoming the hot new career of the year and as a first step employing a data analyst (or scientist) could be the best move to steer your big data mining and analysis endeavor in the right direction.
The three steps of using big data
Data sources: Decide what data are relevant to your business. Forbes has listed 35 free big data sources that can give you a great start.
Data platforms: This is where data is captured and managed and then converted into customer insights. From Hadoop to SASInstitute, Informationweek.com listed these 16 top big data analytics platforms.
Big data analytics tools and apps: this is the 'front end' that business executives, analysts, managers and others in your organisation access to deliver better products and services to customers.You can go for big data analytics software, often bundled with platforms, or put your newly employed data analyst to work. PredictiveAnalyticsToday.com lists 40 platforms and analytics software tools to get you on your way.
The bottom line is businesses intelligence is changing and both large and small companies have everything to gain and nothing to lose by taking all that data that's just sitting there and putting it to work for them.
