Maximising the value of big data analytics

• Big data can help people make key decisions that improve efficiency, etc.
• However, it can also be a hindrance if not interpreted and implemented properly

BIG data technology has impacted our lives in multiple ways in recent years. By analysing large amount of data, scientists, governments and businesses have been able to make important discoveries that have improved our standards of living and changed the way we live and work.
 
Companies today use big data analytics as a way to discover trends to improve the way they conduct business and bring value to stakeholders.
 
Big data sets can go up to several terabytes in size. It can be challenging to analyse massive amounts of data, especially when organisations are under pressure to deliver.
 
The need for insights is often time-sensitive too, which means that data needs to be interpreted quickly and accurately to enable better decision-making.
 
Without the appropriate tools, managing and analysing big data becomes a frustrating and time- consuming process. Here are a few ways how organisations can maximise the value of their big data analytics.
 
1) Blend data
 
Successful use of big data analytics allows organisations to tackle new or current business problems by determining potential pitfalls in a business plan or discovering inefficiencies in operational processes.
 
It can even unravel new market segments, allowing companies to bring new products and services to cater to these segments.
 
To do so, it is important to be able to consider data from across multiple sources to get the best grasp of the situation before making important decisions.
 
In data analytics, time is of the essence. Business leaders and decision makers often require real-time or close to real-time information to make informed decisions.
 
However, it is estimated that 80% of an analyst’s time is spent on preparing and cleaning data for analysis. This leaves only 20% for actual analysis work, and precious time is wasted on preparing the data for analysis.
 
It is therefore important to use a tool that can effectively Extract, Transform and Load (ETL) the data for analysis. We predict that in 2015, ETL tools will become more widely adopted as companies look to ways that will make data preparation an easier process with less need for complex IT infrastructure.
 
A good ETL tool should be able to blend data from across different sources, including public data. This ensures that leaders have all the relevant information in one location, allowing for more efficient decision-making.
 
It also ensures that leaders are getting their information from a single source, reducing the risk of miscommunication.
 
2) Help leaders help themselves

Companies should consider allowing managers and approved staff members to utilise self-service analytics. Many organisations require staff to make a request with IT to get any data analytics, especially big data, done. This often leads to IT being inundated with requests to generate reports.
 
As mentioned, big data analytics allows companies to tackle business problems. These problems are best understood by managers, staff and employees in the field. IT staff may not fully comprehend what is required and can provide reports that mismatches with what is needed in the field.
 
This, coupled with the correspondence time, can result in managers not receiving the information in time to support quick decision-making.
 
By enabling staff with self-service analytics of big data, companies are empowering them to ask questions, identify problems and make informed decisions to get things right.
 
Staff are also able to combine the data with other public information to achieve insights into market segments. Companies also free up IT resources to let them focus on more important and strategic responsibilities.
 
3) Visualisation is key
 
Large data sets can contain complex information like customer profiles, purchase history, multiple touch points, geographical data, etc. This means a massive number of rows and columns if displayed on spreadsheet tools such as Excel.
 
Discovering insights using such a tool can be a daunting task and would take up a lot of time and effort. Users may have problems tracking a specific customer demographic across multiple spreadsheets and could potentially miss out on vital insights that can solve business problems.
 
A good way to address this would be to deploy a tool that allows for visual analytics. Visual analytics presents the data in simple charts and graphs, allowing users to access and view data in an easy to understand format.
 
Using visual analytics also allows users to ask different questions and find their own answers. Today, visual analytics allow users to interact intelligently with their data, and help them to discover information by following their thought processes.
 
4) Plan for the future
 
When selecting a big data analytics tool, it is important to consider the company’s existing IT infrastructure and growth plan.
 
Needless to say, a scalable solution will allow companies to adjust accordingly – include more users when required, reduce seats when there is less requirement – when needed, saving on costs.
 
Another factor to consider is to invest in new and emerging database technologies. Leveraging these emerging technologies can help organisations tackle new classes of analytic problems that could not be addressed previously.
 
Companies may want to tap on cloud computing for instance to bring benefits to a company’s big data analytics capabilities because of its easy scalability and low cost.
 
Recently, options such as Hadoop, a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models, have also become a mainstay in the big data architecture of many companies.
 
Companies need to select a tool that can support and keep up with emerging big data technologies to avoid having to investing in new software, and get people to be trained on it, to suit evolvement in IT infrastructures.
 
Big data can bring much business benefits, helping people make key decisions that improve efficiency, reduce costs, deliver customers satisfaction, etc. However, it can also be a hindrance if not interpreted and implemented properly.
 
Big data analytics brings a never before seen opportunity for companies to drive positive transformation across their organisation.
 
The key is for companies to approach their big data strategies from the ground up by having a good understanding what is required in the field and how to drive informed decision-making that would bring positive business results across.
 
JY Pook is Asia Pacific vice president at Tableau Software.
 
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