Digital transformation relies heavily on data, and organizations face challenges due to the diversity of data sources, formats, structures, environments, and platforms. Organizations must contend with multidimensional data issues when implementing hybrid and multi-cloud architectures. Many enterprises today store their operational data in silos or have hidden it, resulting in large amounts of dark-data.
Dark-data is usually retained by organizations for compliance purposes only and securing and storing dark-data usually incurs greater costs than benefits. It is costing United Airlines almost US $1 billion in lost revenue to collect and store dark-data.1 Enterprise employees are building bottomless lakes of dark-data without any regard for its purpose. Enterprise Strategy Group stated in a report that 47% of all data is dark-data, on average, with a fifth of respondents saying more than 70% of their data is dark-data.2
In terms of restaurant brands, Domino's Pizza ranks among the best in the world. Using the company's AnyWare platform, customers could order pizza online, through mobile apps, smartwatches, TVs, and even social media. In order to gain a holistic view of its customers and global operations, Domino's wanted to integrate information from all channels - 85,000 structured and unstructured data sources in total. It was difficult for them to achieve those goals because they had 11,000 business users, 35 data scientists, and marketing agencies - all of whom wanted to build their own databases. Using Talend as a data fabric solution it is now able to capture data, cleanse it, standardize it, enrich it, store it, and allow it to be consumed by multiple teams. With its modern data platform in place, Domino’s now has a trusted, single source of truth that it can use to improve business performance from logistics to financial forecasting while enabling one-to-one buying experiences across multiple touchpoints.3
Cost is not the only thing that matters when storing dark-data cause its increased data growth can create unstructured data nightmares. Huge volumes of dark-data can make it harder to find what is useful and may mean that you may miss business opportunities. If demand for a piece of information increases, and we have access to it, and we can facilitate its re-use with a common framework then the economic model by which such value is extracted will necessarily be more efficient than one where use is siloed or distinct. Point-to-point integrations and data hubs are no longer feasible solutions as neither of these are suitable when data is highly distributed and siloed. Most, if not all, business data has value, and that value changes over time and in relation to the business mission, goals, and operations. Businesses can exploit unanalyzed operational data as a source of economic opportunities. They can look at using this data to drive new revenues or reduce internal costs. The data businesses hoard can assist them to drive innovation, cutting costs, earning loyalty, and running circles around the competition.
It is impossible to improve business outcomes without real-time access to business entity data. Data fabric solutions facilitate instant access to unified, clean, and complete data that otherwise would remain stuck within your enterprise, unusable and inaccessible. Business decisions can be made more intelligently, customer experiences can be enhanced, and operational outcomes can be enhanced. Data challenges arising from a hybrid data landscape will be addressed by this solution. By acting as a virtual connective tissue between data endpoints, it strikes a balance between decentralization and globalization. The system ensures that your diverse types of data can be combined, accessed, and governed efficiently. Business value only comes from contextualized data that can be accessed by all users or applications in an organization.