Being a data-driven organization used to mean that executives made their decisions based on some amount of data instead of gut instinct — whether that data took the form of a spreadsheet, a database report, or a dashboard. Today, being data-driven means having the ability to use every bit of data, structured or unstructured, on-premises or in multiple clouds, in motion, or at rest, anywhere in the world, to drive the next best action or decision of everyone in the organization.
As organizations work to become this type of data-driven organization, the following six steps will ensure a smooth data journey across any platform, cloud, or application.
1. Change the culture
What the lines of business (LOBs) want to do with data grows ever more complex, and the timeframes they need to do it in grow ever shorter. This makes it impossible for organizations to rely on the traditional approach of LOB teams asking IT to provide them with the data they need. Instead, the LOBs and IT must coordinate closely on what the LOBs need to do with the data and who has responsibility for what data and which processes. IT must understand the new tools and solutions on the market that make it possible to distribute data management and governance to the teams while still maintaining centralized control over infrastructure. It is also important to dispense with the ingrained notion that data belongs to this team or that team. All the data across the organization belongs to everyone in the organization. Collaboration is how an organization wins.
2. Engage data governance and compliance teams from the beginning
While all data in the organization belongs to everyone, it must be subject to internal and external compliance requirements and evolving privacy regulations. This means data governance and compliance must be part of the journey to become data-driven from the very beginning. Enterprise data platforms must help data teams understand which datasets contain personally identifiable information, intellectual property, and other sensitive information. Where is this sensitive information stored, who has access to it, and how is that access managed to ensure only the right people can access it at the right time from the right location? The data platform must also provide insight into data lineage and data transformations for the entire data lifecycle, across the entire data infrastructure.
3. Embrace public cloud and cloud native data architectures
Use the fully managed and on-demand public cloud capabilities to create an agile data architecture for your business. Capabilities, pricing, and geographic availability differ from one public cloud to another, so a multi-cloud approach enables developers to use the best cloud for each workload and data set to balance performance and cost, and drive innovation. As such, this reduces the temptation for developers to turn to shadow IT to solve their application challenges.
4. Turn the on-premises data center into a true private cloud
Despite the appeal of the public cloud, companies will rely on on-premises applications and keep data on premises for years to come. To become data-driven, enterprises must improve how they manage and derive insight from their on-premises data. The solution is to turn the physical infrastructure — monolithic deployments of tightly coupled compute and storage — into a true private cloud with all the flexibility and agility that the public cloud provides, but with all the controls the enterprise needs.
5. Connect private and public clouds for a true hybrid data model
With the on-premises infrastructure now an agile private cloud, it’s time to connect the private cloud with multiple public clouds to create a true hybrid data model. This model enables enterprises to manage data consistently – everywhere – and gain real-time insight from all of it. It also provides full flexibility to automate how workloads and data move to any environment, anywhere in the world to optimize performance, security, and cost.
6. Unleash developers and users: The tools matter
Simply creating the new hybrid data capability isn’t enough. Data teams must have the analytics and governance tools to take advantage of all this access to data. The tools must support all data types and all types of analytics on data-at-rest and data-in-motion and enable them to easily leverage purpose-built and integrated services to meet the needs of their specific use cases. Finally, the tools must make it possible to automate, automate, automate — which in the end is the only way teams can truly take advantage of all the massive amounts of data at their disposal.
Conclusion
Becoming a truly data-driven organization will take time. And creating a hybrid multi-cloud infrastructure to take advantage of all data can be a daunting process for even the most experienced enterprise IT teams. But in today’s hyper-competitive environment, it is essential to develop this capability as soon as possible. So, it is essential to find partners that truly understand the challenges that large, globally distributed enterprises with petabytes of data face and that are accustomed to helping these organizations transform infrastructure with minimal disruption.
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