Becoming a “data driven” company is something that we hear more and more in the statements made by CIOs and those responsible for digital transformation. Being able not only to collect all the data generated by the company, but above all to know how to interpret it, understand the story it tells and make decisions about it, however, has become one of the main challenges they face.
Today, becoming data driven has a series of implications at a strategic, technological and cultural level that are directly linked to the productivity and performance of businesses, as well as their ability to remain competitive in the market. In this context, Cloudera has shared six steps that can help any company start a digital transformation process in this field.
Start at the beginning, the change of culture
The different business units of the companies demand data projects, increasingly complex and in shorter times. This makes it impossible for organizations to rely on a traditional approach where teams ask IT to provide the data they need. Now more than ever, the two need to coordinate closely to establish what the organization should do with the data and who is responsible for each part of the process.
The IT department must know the best tools and solutions on the market that allow data management and governance to be distributed to teams, while maintaining centralized control over the organization’s infrastructure. It is also important abandon the entrenched conception that data is the property of one department or another. All the organization’s data is a common good. Collaboration is the only way an organization wins. That’s where data analysis software are very useful for organizations.
Engage governance and compliance teams from the start
While all organizational data belongs to the collective, it should be subject to internal and external compliance requirements, as well as evolving privacy regulations. This means that data governance and compliance must be a crucial part of the data-driven journey from the start. Enterprise data platforms must help data teams understand and identify personal information, intellectual property, and any other sensitive confidential information.
At this point, companies must be able to answer key questions: Where is this sensitive information stored? Who has access to it? How is access managed to ensure only the right people can access it at the right time from the right location? It is the responsibility of the data platform to provide information about the lineage and transformation of the data throughout its lifecycle, and across its entire infrastructure.
Embrace public cloud and native data architectures
To move towards a Data Driven culture, companies need to take advantage of the capabilities of the public cloud and thus create an agile data architecture for the business. Capabilities, pricing, and geographic availability differ from one public cloud to another, so a multi-cloud approach allows developers to use the best cloud for each workload and data set, balancing performance and availability. cost to drive innovation. This reduces the temptation for developers to turn to shadow IT to solve their application challenges.
Convert the server to a true private cloud architecture
It’s important that despite the lure of the public cloud, businesses continue to rely on on-premises applications and keep their data on-premises, as needed. However, to become Data Driven, an essential requirement is that companies improve the way they manage and obtain information from their local data.
The solution is to convert the physical infrastructure into a true private cloud with all the flexibility and agility that the public cloud provides, but with all the controls that the company needs.
Connect public and private clouds to achieve a true hybrid model
Another aspect to consider is the connection of the private cloud with multiple public clouds to create a true hybrid data model. This hybrid model allows companies to manage data consistently and get insights from all parties in real time.
It also provides full flexibility to automate how workloads and data are moved to any environment, anywhere in the world to optimize performance, security, and cost.
Implement the right tools to achieve automation
Data teams must have the necessary analytics and governance tools at their disposal to take advantage of data access. These solutions must handle all types of data and all types of analytics, as well as enable teams to easily take advantage of integrated and purpose-built services to meet the needs of each specific use case.
Finally, the tools need to enable automation, which is ultimately the only way teams can truly harness the massive amount of data at their disposal.
