Ways to Smooth the Bumps on the Data-Driven Path

Being a data-driven organization means that CEOs make their decisions based on some amount of data rather than instinct—whether that data takes the form of a spreadsheet, a database report, or a dashboard. Today, being data-driven means having the ability to use every piece of data, structured or unstructured, on premises or in multiple clouds, on the move, or at rest, anywhere in the world, to guide the next best action or decision every person in the organization.

As organizations work towards becoming this kind of data-driven organization, the following six steps will ensure a seamless data journey across any platform, cloud, or application.

1. Culture change

What Lines of Business (LOBs) want to do with data is getting more complex than ever, and the time frames they need to do so are getting shorter than ever. This makes it impossible for organizations to rely on the traditional approach of LOB teams of asking IT to provide them with the data they need. Instead, LOBs and IT must closely coordinate what LOBs need to do with data and who has responsibility for data and operations. IT must understand the new tools and solutions in the market that make it possible to distribute data management and governance across teams while maintaining central control over the infrastructure. It is also important to dispense with the overarching notion that the data belongs to this or that team. All data across the organization belongs to everyone in the organization. Collaboration is how an organization wins.

2. Engage data management and compliance teams from the start

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 that data management and compliance should be part of the journey to becoming data-driven from the start. Enterprise data platforms should help data teams understand which data sets contain personally identifiable information, intellectual property, and other sensitive information. Where is this sensitive information stored, who has access to it, and how is this access managed to ensure that only the right people can access it at the right time from the right location? The data platform should also provide insight into data strain and data transformations for the entire data lifecycle, across the entire data infrastructure.

3. Embrace native and public cloud data structures

Use fully managed and on-demand public cloud capabilities to create an agile data architecture for your business. Capabilities, pricing, and geographic availability vary from public cloud to public cloud, so the multi-cloud approach enables developers to use the best cloud for each workload and dataset to balance performance and cost and drive innovation. As such, this reduces the temptation for developers to turn to Shadow IT to solve their app challenges.

4. Turn your local data center into a true private cloud

Despite the allure of the public cloud, companies will rely on on-premises applications and keep data on premises for years to come. To become data-driven, organizations must improve how they manage it and extract insights from their local data. The solution is to transform the physical infrastructure – the monolithic deployments of tightly interconnected computing and storage – into a true private cloud with all the flexibility and agility that a public cloud provides, but with all the controls an enterprise needs.

5. Connect private and public clouds for a true hybrid data model

As the on-premises infrastructure is now an agile private cloud, it is time to connect the private cloud with multiple public clouds to create a true hybrid data model. This model enables organizations to manage data constantly – everywhere – and gain real-time insights from it all. It also provides complete flexibility to automate how workloads and data move into any environment, anywhere in the world to improve performance, security, and cost.

6. Unleash Developers and Users: Tools matter

Simply creating a new hybrid data capability is not enough. Data teams must have analytics and governance tools to take advantage of all this access to data. Tools should support all types of data and all types of analytics on sleep and data in motion and enable them to easily leverage integrated, purpose-built services to meet the needs of their specific use cases. Finally, the tools should enable automation, automation, and automation—ultimately the only way teams can truly benefit from all the massive amounts of data available to them.

conclusion

Becoming a truly data-driven organization will take time. Creating a hybrid, multi-cloud infrastructure to leverage all the data can be a daunting process even for the most experienced enterprise IT teams. But in today’s highly competitive environment, it is essential to develop this ability as quickly as possible. Therefore, it is essential to find partners who truly understand the challenges faced by large, globally distributed organizations with petabytes of data and who are used to helping these organizations transform infrastructure with minimal disruption.

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