Five ways to maximise the value of business data

Five ways to maximise the value of business data

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Lisa Stewart of Teradata explains how third-party analytics can enable faster innovation and increased productivity 

Guest contributor |

With businesses navigating economic uncertainty, supply chain disruptions, employee turnover and changing customer experience needs, “doing more with less” has become a familiar refrain. To answer this call, organisations are searching for efficiency gains and are turning to data to unlock cost savings.  

Harnessing the power of data is critical for faster innovation and increased productivity. The Forrester study, The Business Impact of Data Intelligent Management, found that data-driven businesses are 58 per cent more likely to beat their revenue goals than their non-data-driven counterparts. Teradata’s experience in delivering analytics for hundreds of the world’s largest enterprises provides us with a unique perspective on how top businesses unlock data insights to drive productivity, efficiency and growth. There are five ways that leading organisations maximise the value of their data to do more with less. 

Firstly, they can integrate their data without replicating it. Partial data sets give partial answers. Integrating information from various different data types and sets is critical to enabling fully-informed decision-making and gaining a 360-degree perspective of customers and the business.  

Data has become more and more important, and this is being understood by businesses worldwide. For example, Netherlands-based toy retailer Intertoys has been using Teradata’s solutions to integrate third-party data. When asked about his experience, Intertoys IT manager Robin Tichler said: “We’re able to use outside external data so that we can see patterns between trends and sales that we don’t normally see, such as the success of a sporting event or television show and the effect these activities have on product purchases”. 

Analytics platforms that use in-database processing can provide significant performance improvements and deeper insights over traditional analytics approaches by blending and analysing large data sets without moving them out of a database. The easy connection and analysis of data within low-cost object stores – rather than pulling data into a seperate environment – cost-effectively delivers on the promise of unified data intelligence. 

Secondly, organisations can query large data sets rapidly and cost effectively by performing ‘what-if’ scenario analysis. This can be done via analytics platforms such as Teradata VantageCloud, which has protections in place to ensure predictable performance and prevent experimentation from impacting existing quality and workloads. Our analytics platform provides companies with the safety of knowing that they will only be charged with a low cost per query rather than accidentally spending $100,000 or more with a poorly constructed query against a large data set. 

Data needs to be made available everywhere to help inform organisations to make faster and better decisions. This includes all types of data such as internal and external data, and structured and unstructured data that supports decision-making with machine learning and prescriptive analytics. Multinational consumer goods company Unilever has been using the Teradata VantageCloud platform to support its 27 business services. It is now able to run hundreds of reports thousands of times each month to make more-informed business decisions.  

Thirdly, the recent Covid-19 pandemic highlighted the need to centralise data governance across functions to rapidly respond to unplanned events. Organisations that centralise governance can ensure data quality and be highly responsive to the changing market conditions. Analytics platforms that deliver easy-to-use management tools for self-service provisioning, computer and storage utilisation tracking, database monitoring and alerting, backup and restore functionality, and disaster recovery reduce the risk of unforeseen costs and help organisations be more agile and responsive to change. 

Fourthly, to do more with less, organisations need to carefully manage their resources to meet demand. When it comes to data, this means selecting an analytics platform that elastically scales computer and storage resources to handle peak workloads. It also means giving users the ability to prioritise their most critical workloads by configuring business rules that ensure the right resources are dynamically applied to the right workloads at the right time. Data elasticity ensures organisations achieve economies of scale and keep costs low by only paying for the resources that they use. 

Finally, companies should leverage the cloud and a connected data ecosystem to reduce software costs. Migrating data analytics solutions to the cloud can keep the number of software vendors to a minimum and deliver software as a service. Selecting cloud-based analytics platforms that are open and connected with many of today’s leading data services, as well as artificial intelligence and machine learning modelling tools, provides the flexibility to do more with the systems that organisations already know and love. 

Leveraging connected, cloud-based analytics platforms helps you harness data to identify new ways to do more with less. Change can be uncomfortable but maximising your data lets you pinpoint areas for productivity improvements and shape your organisation’s transformation to a more efficient future.   

Learn more about Teradata’s data analytics platform at:  

Lisa Stewart is senior vice president of worldwide partners and alliances at Teradata 

This article was originally published in the Winter 2022 issue of Technology Record. To get future issues delivered directly to your inbox, sign up for a free subscription

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