Home Business Insights & Advice Your company’s cloud data platform success hinges on proper governance

Your company’s cloud data platform success hinges on proper governance

by Sponsored Content
18th Aug 20 10:44 am

Data is now widely considered to be the lifeblood of modern enterprises. It’s no surprise that organizations have made data and analytics key aspects of their business growth strategies. Last year, 81 percent of UK companies said that they were increasing their investments in big data efforts. Globally, big data and business analytics solutions are projected to make revenues totaling $274.3 billion by 2022. Despite this, only 30 percent of companies claim to be getting enough value out of their spending.

Success in big data relies on a variety of factors. A crucial part of any effort is having capable infrastructure. Companies should be able to manage the various computing tasks involved in the process. As some business leaders have discovered, simply using existing systems can stymie their efforts as legacy technologies can fall short of what’s needed. New cloud-based solutions have since emerged to make it easier for companies to help them migrate to this type of infrastructure.

Any team or organization can now opt to use a cloud data platform to handle their requirements. These platforms feature specialized architectures and built-in software components to facilitate data collection, processing, storage, and analysis. As cloud-based solutions, they are also scalable and readily deployable, advantages which effectively complement the agile methodologies that many organizations now employ.

But alongside adopting these solutions, data teams would also do well to take data governance seriously. Even with capable and sophisticated tools, analytics initiatives are bound to fall short if the organization’s data is disorganized, inaccurate, incomplete or unsecure. Vigilant governance minimizes the possibility of collected data to go unused or to be accessible to the wrong parties.

As such, organizations looking to succeed in big data must ensure that they have capable infrastructure and governance frameworks in place.

Taking advantage of the cloud

From an infrastructure standpoint, using cloud data platforms simply makes sense. To start with, the various functionalities and services cloud data platforms offer now essentially encompass the end-to-end requirements of organizational business analytics programs, from collection to visualization.

Even line-of-business users can easily build their own data pipelines by connecting various data sources. This provides for smoother workflows, since all required data and tools are managed under one intuitive platform.

In addition, cloud platforms offer scalability. They make the question of resource requirements irrelevant from the onset. Companies can simply start out conservatively and just scale up as demand for resources increases. For example, if there’s a sudden influx of data that needs to be processed, the team can upgrade storage service tiers or tap more computing time and power to crunch the information. This ensures that the effort has ample computing resources to deal with any task.

Cloud platforms also help minimize downtime and even help in disaster recovery. Legacy infrastructure is dependent on dedicated machines and servers so a fault in one, say a database server, can bring an entire operation to a halt. Cloud platforms are designed to be highly available, so downtime is rarely an issue. They also offer backup and redundancy features that allow data to be recovered or rolled back in case anything untoward happens.

Keeping governance at the core

With a cloud data platform covering the infrastructure side of things, data teams should also optimize their information governance capabilities and processes. The convenience that cloud platforms provide can unnecessarily make data teams complacent and even careless when handling data. Since the technology already provides many of the requirements, it’s easy for users to overly rely on the tools they have.

But as with most computing tasks, data efforts are garbage in, garbage out. Using poor quality data results in imprecise or otherwise useless analyses, undermining the entire undertaking. Governance aims to prevent the errors and redundancies that cause poor data quality. For example, it’s possible for organizations to gather data from even hundreds of sources, including their enterprise applications, websites, and even Internet-of-Things devices in the workplace. As such, there is a rise in the volume and diversity of data that companies are now able collect.

Having governance policies that require all data to be tagged with corresponding metadata such as what the information is about and their sources, prior to transmission to your cloud platform, can greatly help maintain the usefulness and accuracy of the data.

Aside from these data-specific concerns, analytics teams should also be mindful of legal issues such as privacy compliance. Regulations like the GDPR specify how and where various parties can use every type of information, so it’s important to comply with these provisions. Particularly important in governance is the inclusion of guidelines on the use and access to personal, financial and other sensitive data. Most cloud platforms have access management features that can identify and limit a user’s access and use to the data and tools. Logs can also track all user activity to allow for an extra layer of accountability.

It’s also possible for cloud data to be geographically distributed, and some laws may limit where user data may be transmitted or stored. Data recovery settings may also be set to keep copies of information for extended periods of time which can go against retention provisions and the right to erasure.

Combining both for results

Any effort requires the right combination of tools and methods to be successful. In the case of big data, cloud data platforms provide the necessary tools that are needed in the various tasks and processes involved in getting value out of data. Governance provides the controls to ensure that efforts stay on point and limit the potential issues that may arise from the effort.

When both are combined and applied, data teams can rely on high quality data that should result in accurate and more impactful insights from which the business can benefit. Data costs can also be reduced as data teams gain efficiency and minimize the risk for errors. Ultimately, organizations are looking to get returns in their data spending. Being able to maximize their use of cloud platforms through effective governance should greatly contribute to the success of their efforts.

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