IT Focus Area: data
July 23, 2021
3 Key Considerations for Building a More Modern, Agile Data Platform
The need to share data has always been critical for business. However, during the 2020 global pandemic, this need grew exponentially—and there is no going back.
Many organizations were already struggling with legacy data and analytics solutions that no longer met the needs of their business. Suddenly, CIOs everywhere needed to strategize and set up secure, highly-efficient work from home and data sharing capabilities for all stakeholders—across more endpoints than ever imagined.
When the world changed, so did the way we move, consume, secure, leverage and manage data.
As the volume, variety and velocity of data continues to grow, how can companies gain the ability to manage their data, regardless of where it lives and how much there is? And how will they maintain the agility they need to leverage it across data silos?
Build a modern data platform
Building a modern data platform and appropriately treating data as a strategic asset can help you make data-driven decisions quickly and ensure you are getting the most value out of your data. This strategy ultimately leads to better business outcomes.
3 keys to developing a data-focused culture
But where should an organization with an outdated data warehouse begin? Start by developing a data-focused culture and strategy with these key considerations:
1. A modern approach to continuous intelligence
Gartner defines continuous intelligence as, “a design pattern in which real-time analytics are integrated into business operations, processing current and historical data to prescribe actions in response to business moments and other events.” It is estimated that “by 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.”1
The modern data age demands a carefully planned strategic framework to deliver on the promise of deep, transformative insights. Building a modern data and analytics platform allows you to gather, store and process data of all types and sizes from any data source. In fact, an agile, modern data platform is key to harnessing your data’s power to reveal patterns and make predictions—all to fuel digital transformation.
An agile, modern approach give you the ability to:
- make smarter decisions through real-time data and advanced analytics
- enhance your situational awareness with always on, continuously learning solutions
- unlock valuable insights, making it easier to identify trends and risks
- reduce business costs and optimize operations
2. Democratized access
Data democratization is at the core of self-service analytics because it helps your users seamlessly access data that can be used to make informed business decisions.
Quite simply: it means everybody has access to the data they need and there are no gatekeepers. When you allow data access to any employee at your company—regardless of their position—it empowers individuals at all levels to use the data in their decision making. Ultimately, this access can help create a data-driven culture of innovation throughout your organization.
By increasing the access and usability of your organization’s data,
- free up time for your data scientists
- provide accurate, real-time insights
- improve operational efficiency
3. The ability to scale dynamically
These days, there’s no telling how much data you will need to manage for your organization. When you have a platform built for the cloud, that scales as you need it, you no longer need to anticipate storage hardware, software upgrades or capacity issues as you would with traditional infrastructure. This provides unlimited flexibility for your enterprise, so you can adapt to meet changes on demand, which will save you resources and budget.
Beware of data silos
Before you get your arms around any of these considerations, you will need to take a hard look at any potential data silos within your organization.
According to a recent report from Forrester, 60% of organizations find it challenging to manage their data.2
This is no surprise because even when organizations recognize the value of their data, their data is often accessible by only one department and isolated from the rest of the company. This can result in a lack of transparency, efficiency and trust across the enterprise.
So, what causes data silos? And what can you do to overcome them?
Common causes of data silos and professional tips for change
Poor technology is often a main culprit of creating silos. Data cannot pass between departments when there is no access to the right kind of technology or applications that can handle a quick transfer of information. Data trapped in a separate database that is not accessible by the main enterprise system is also a concern.
Pro tip: It may be time to invest in cloud services or agile applications to make up for the shortcomings in your legacy systems.
Organizational growth can also cause silos. When a company becomes too large, or has recently been involved in a merger or acquisition, it becomes more difficult to share data between departments, office locations or employees. You may encounter infrastructure issues, or certain teams may not want to release data to other teams—especially if they are concerned about security access and controls.
Pro tip: You may want to consult with an experienced third-party advisor who has helped thousands of companies across multiple industries securely leverage their data to the fullest—even in tricky situations such as a merger or acquisition.
Fluctuating and disparate data is also responsible for silos within an organization. When different databases are isolated from each other, you need a complex web of technologies for data integration, transformation, normalization, aggregation and data analytics to get data in the hands of your users. Managing these technologies and all the connection points becomes a full-time job, so there is not enough time to actually work with the data to gain Insights. Governance and security issues are also common with this siloed approach.
Pro tip: Data integration platforms and frameworks can help you address these issues and bring it all together. Finding the exact right platform for your company will help you simplify and streamline all your data, and, working with an experienced advisor to help you do just that can also prove beneficial.
No matter what industry you’re in or where you are on your data journey, adhering to these three key considerations, and following the pro tips, will help you establish a sound foundation for building a modern, agile data architecture.
1) Kasey Panetta, Gartner—Feb, 2019, "A Data and Analytics Leader’s Guide to Data Literacy"
2) Forrester—May, 2019, "AI Experiences A Reality Check"