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Data’s importance in modern business cannot be overstated. Increasingly, teams are using data, and the insights they’re capturing from it, to innovate across all areas of the organization, from customer and employee experience to internal business processes and supply chain optimization.
But several challenges continue to inhibit data initiatives. IT leaders in Foundry’s 2022 Data & Analytics study identified their top five pain points as: data quality; security and governance; data analysis; data integration; and data preparation/transformation. Collectively, these challenges point to the need to modernize underlying data infrastructure.
“Innovation brings data management challenges and opportunities for IT leaders,” says Kieran Gilmurray (@KieranGilmurray), CEO of Digital Automation and Robotics Ltd. “Technology offers a smorgasbord of structured and unstructured data to pick from, but also opens a world of complexity. Data advantage will only be possible if organizations can harness their data.”
We asked the CIO Experts Network, a community of technology influencers, about the most important data management considerations for IT leaders who want to accelerate innovation across their organization. They identified three areas as critical: core building blocks, security and governance, and culture.
Core building blocks: Infrastructure, integration, and scalability
Doing more with your data begins with a strong data-management foundation. Experts describe some of the most important components of these building blocks.
“There are three crucial areas that IT leaders must tackle to take back control of their data management initiative: data acquisition, data pipeline automation, and [cryptographic] key management,” says Peter Nichol (@PeterBNichol), Chief Technology Officer at OROCA Innovations. “Without data, there are no insights to be gained. Therefore, gaining access to that data through data acquisition becomes a critical path activity on day 1.”
As organizations acquire more and more data, integrating all that information so it can be used across the business is an important next step.
“Unification of data is of paramount importance in enabling innovative business use cases across organizations,” says Sridhar Iyengar (@iSridhar), Managing Director with Zoho Europe. “This means [making it] not only simple to bring data together, but preparing it in the right way [so it can] be analyzed to provide an accurate view across the entire organization. This brings extremely valuable benefits.”
Isaac Sacolick (@nyike), President of StarCIO and author of Digital Trailblazer, recommends investments in what he calls “digital transformation force multipliers,” which include DevOps tools for automating infrastructure; data intelligence capabilities that leverage unstructured data; and enhanced employee experiences. “All three of these investments are building blocks that even midmarket and small businesses need to compete in a highly competitive, digital, disruptive, and data-driven world,” he adds.
Will Kelly (@willkelly), content and product marketing manager focused on the cloud and DevOps, echoed the importance of DevOps as a key data-management consideration. “Accelerating innovation starts with IT leaders getting data in their DevOps or DevSecOps pipelines,” he says. “They also need to get the back-end data under control in their production cloud environments. When IT leaders gain mastery over toolchain and cloud back-end data, they can plan an accelerated path to innovation.”
Making data more visible and more accessible across the data estate will enable the types of intelligence and insights that “power the innovation engine in many companies,” says Gene De Libero
(@GeneDeLibero), Chief Strategy Officer at GeekHive.com. “The result is data agility, where data is shaped, surfaced, and shared based on the needs of the business and the people it serves.”
Robust security and governance are table stakes
Another vital component of modern data management is security and governance. These concepts need to be built into the planning, development, and deployment of any infrastructure and tools for collecting, storing, managing, and analyzing all forms of data.
“Good governance does so much more than compliance,” says Michael Bertha, Vice President at Metis Strategy. “If you think of data as automobile traffic, governance is the system of signs, lights, lines, limits, exits, and parking rules that gets everyone where they need to go without crashing into each other.”
Bertha stresses the importance of a cross-functional approach to data governance. “Data governance boards should include representatives from every business unit or function [to] design policies and assign governance roles that not only protect enterprise data but drive innovation and business value,” he says.
Managing historical information is an important aspect of any governance strategy, says Bob Ward (@bobwardms), Principal Architect with the Azure Data Engineering team at Microsoft. “For compliance needs that require long-term retention of data, I need to define where I’m going to keep all of this and how I can access it when I need it,” Ward says. “To meet the compliance requirements of your industry, your company, your government, whatever it may be, you need to retain the data in a way that's easy to access, but also compliant and secure, across cloud and on-premises environments.”
Data controls will ensure that high-quality data is available to decision makers when it’s needed, says Gilmurray, from Digital Automation and Robotics. “For that to happen, data needs to be stored and secured to preserve its integrity, and then analyzed and communicated to maximize its business utility,” he says.
Building a data-driven culture is critical to success
As with most other aspects of digital transformation, a successful data platform requires cultural change in addition to modern technology and process improvements.
“The key to any data management scaling is in the ability to socialize the effort,” says Frank Cutitta (@fcutitta), CEO & Founder of HealthTech Decisions Lab. “History tells us that stakeholders need to be trained to trust and apply the data insights for competitive advantage.”
One critical set of stakeholders is the leadership team, who set the tone for a data-driven culture. “Successful organizations understand effective data management comes from leaders that … drive the data forward through innovative leadership, not through technology alone,” says Peggy Smedley (@connectedworld), editorial director and president of Specialty Publishing Media.
Importantly, modern data management also presents an opportunity to align data strategy with diversity, equity, and inclusion (DEI) initiatives. Diversity expands the innovation opportunities that stem from data because it expands the types of insights you can derive from it.
“You need people from different paths in life to be able to understand the variety of messages in the data you have,” says Pamela Rucker (@pamelajrucker), a CIO advisor and instructor with Harvard Professional Development. “And you need ecosystems to expand your capabilities so that you can capitalize on opportunities when they show up in your data.”
“It is time to consider the human side of the equation and how your teams access and manage data,” adds Debra Ruh (@debraruh), CEO of RGI and Executive Chair of Billion Strong. “Build accessibility and human-centered design principles into those data elements management efforts. We all win with accessibility efforts.”
Choosing the right platform
Zoho Europe’s Iyengar notes that choosing the right platform – and platform partner – greatly influences data-management success. He recommends that CIOs ask a series of key questions to assess whether a platform provides a foundation for innovation:
· Does the platform enable optimization of processes across your business?
· Does it enable unification of data and services?
· Does it enable customization and scalability?
· Does it provide fast return on investment?
· Does it provide the right type of insight to the right audience when they want it?
· Is it flexible to offer applications and services which can be introduced as your business requirements fluctuate?
· Is the vendor aligned with you culturally and with complementary value?
Getting the right answers to those questions – and choosing the right platform and tools to support your data-modernization journey – are the keys to success.
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