With a clear vision in mind, you can build data integration processes aligned with your strategic objectives and measure your progress along the way. A robust data strategy is rooted in clearly defined business objectives and specific use cases that help drive value, along with continuous monitoring, ongoing improvement, and agility to adapt as your business objectives evolve and new challenges arise.Īs you build out your data unification strategy or goal, consider what data your organization collects, who needs access to it, how they will use it, and why it drives your business forward. More than two-thirds of companies struggle to realize tangible benefits from data - and that’s often the result of poorly defined goals and mismanaged strategy. Rather than extensive data replication and movement, real-time connectivity relies on APIs to seamlessly connect various sources - an approach taken by more than half of organizations today.Īs you work to remove barriers to data unification and deliver better business results, consider the following three strategies to leverage real-time connectivity platforms - and empower your organization to move forward in its digital journey. Real-time data connectivity platforms allow businesses to assemble data from different sources in a single location, enabling direct access to data at its source. How can your business streamline, simplify, and save costs on data unification? Three Strategies to Move Data Unification Forward Faster When enterprises empower users to access and analyze data without delays, they can turn information into meaningful insights that drive more informed decisions and, ultimately, more value for the business. Organizations must find a way to unify their data without incurring exorbitant expenses or bogging down their cloud infrastructure. The same problems pop up for retailers dealing with large, rapidly changing volumes of transactional data or enterprises that constantly update data on their human resources platforms and ERPs. Such a high volume of data generation quickly becomes cost prohibitive to efficiently store and query. When these fees compound, they coalesce into a digital dam that clogs up even the best-intentioned data strategy.Ĭonsider the consumer packaged goods (CPG) industry, which generates massive amounts of data encompassing everything from inventory to point-of-sale to supply chain data, as well as customer information from online interactions, loyalty programs, and various other touchpoints. While cloud storage rates may appear reasonable, enterprises that generate massive amounts of data can face cost issues when moving, storing, and querying data. More than two-thirds of organizations say data storage accounts for 25% of their total cloud costs, and nearly one-fourth said it costs more than half of their budget. For example, ETL (Extract, Transform, Load) pipelines that automatically extract data from various sources, transform it to the desired format, and load it into a target system or data warehouse, cause significant delays and impacts on data quality that can result in stale, outdated, or inaccurate data information.ĭata that are replicated, transferred, and stored take up significant cloud space and, more importantly, budget that could be better spent on digital improvements and innovations. The increased volume and complexity of enterprise data have led to ballooning costs for talent, computing, and storage infrastructure.Īs a result, traditional integration processes are no longer enough. In today’s cloud environment, enterprise data is generated in different formats, structures, and locations across various applications and networks - a web of digital touchpoints that can make data integration a daunting task. The Data Dam That’s Clogging Up Data Management These barriers cause businesses to miss out on opportunities to streamline processes, reduce costs, and make data-driven decisions that could propel them ahead of competitors. Traditional approaches to data management, storage, and connectivity aren’t working. A staggering 93% of IT decision-makers say storage and data management complexities hinder their digital transformation efforts, while 56% of business leaders say managing data-operating costs is a major pain point. The high cost and complexity of data management are holding businesses back from achieving their digital ambitions. In today’s data-driven economy, organizations are tasked with managing and extracting insights and generating value from vast amounts of enterprise data. Enterprise data is expected to more than double by 2026, with cloud data storage growing by nearly 20% annually.
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