Local organisations across New Zealand will not achieve maximum return on their data investment until they can remove the barrier of siloed data, according to the recent Teradata Data Analysis Index.
The Index revealed that siloed data sets were a major barrier to effectively implementing a robust data analytics program for 41 percent of respondents.
“Organisations can tend to pigeonhole big data projects into specific departments or functions and only use data sets from these areas,” says Alec Gardner, managing director, advanced analytics, Teradata A/NZ.
“This stops organisations from seeing a complete picture. The good news is that organisations can fix this issue. They need to include data from different departments and merge all data sets together.
“This helps create more meaningful insights, and delivers a more comprehensive view of the information, letting organisations make smarter, more effective decisions.
“Most of the value of big data projects can only be realised by breaking down silos through a data integration initiative.”
For example, Gardner says a company that wants to understand customer behaviour more deeply needs to examine data from a number of different systems.
From the marketing automation system and customer relationship management (CRM) system to the e-commerce or invoicing system and more, customer information is held across a variety of silos.
Data integration (breaking down the barriers between those silos) is the only way to truly understand the customer.
“Data integration simply means turning various data warehouses and other repositories into a single, central repository that contains all the significant parts of the organisation’s data,” Gardner adds.
“It can be created iteratively and should constantly evolve to suit new uses. Doing this can save money in many different ways, since the data gathering, storing and analysing processes can be streamlined and economies of scale can be exploited.”
For Gardner, integrated data warehouses deliver significant value but the process of integrating disparate data sources can be expensive and seem complex, particularly when it comes to calculating return on investment (ROI).
“Companies must get smarter about aligning the data integration challenge with the payback,” Gardner adds.