The ability of businesses to harness their data and innovate is hence now more vital than ever. But data transformation is getting harder, not easier, as organizations grapple with an increasing deluge of data, alongside legacy systems and messy data structures accrued over the years. This is where the cloud can make a pivotal difference, according to panelists at the latest CDOTrends Digi-Live! Summit Series earlier this month.
Karthikeyan Rajasekharan, the APAC sales director of data analytics and artificial intelligence at Microsoft explained: “Great insights come from asking questions, and there is always a cost associated with [answering] questions within a business context. But with the advantages that you have in the cloud, customers can ask better questions – including questions that they were not able to ask before.”
The power of the cloud
Rajasekharan related how a customer he worked with had seven years’ worth of CCTV footage of their business due to compliance regulations. To reduce the cost of maintaining the vast physical tape archive, the customer decided to upload the footage into the cloud.
This also allowed them to answer a pertinent question by leveraging computer vision and machine learning in the cloud: How many of my customers smile as they step out of the store? Rajasekharan observed: “That is a question that was not possible or was at least prohibitively expensive to answer previously. [But with the cloud] you can do that.”
Ram Thilak, chief data scientist and global head of data science at automotive supplier Inchcape, agreed. “Whenever we talk about digital innovation, the cloud [is invariably part of the solution]. The cloud helps us to make the data and the entire landscape that we have more malleable. The biggest challenge we had before was: How do you connect and integrate everything? This challenge has been addressed by the cloud. Whenever we talk about digital innovation, it is important that we [include] the cloud.”
This presupposes the availability of data, of course. “Data is critical and the fundamental pillar for any digital innovation. If you think about digital innovation, data comes along with it. It's not a separate part of it. [Data is crucial for] any organization to excel and unlock the value that they have. It is also vital for them to go on an innovation journey as well,” said Thilak.
Getting data to work
But what does the data modernization journey look like? One notion highlighted by Rajasekharan is the democratization of data, which serves as the linchpin for powering data-driven decision-making. He cautioned, however, that data democratization is more difficult than it sounds.
“[While it sounds] simple, [data democratization] requires a fair amount of work to get to that desired outcome. How do I make sure that the data is available? How do I make sure that it is governed with the highest regard for customer data, privacy, and security?” he said.
Rajasekharan pointed to Microsoft’s data modernization journey to manage data as a strategic asset, and how it resolved issues such as internal data “chaos” and duplicate internal data. This saw the software giant adopting a phased approach with federated data lakes for finance and maintained by a team dedicated to maintaining the data lake as a service and gradually introducing it into other parts of the organization.
Stakeholder engagement is vital for Sean Lam, the head of data science at SingHealth. He pointed out that stakeholders need to see the value of data, and how clean data can support various initiatives within the organizations.
“I'm sure a large part of the population will [agree to the use of their data] if it is used to cure cancer or to eradicate COVID. I would personally be more than happy to share my data for you to use if I can see the value. [Without first demonstrating the value,] I think then there will be a constant struggle between the use of customer data beyond its primary purpose, which in the case of healthcare would be providing care to patients.”
Moving ahead with data
Of course, data democratization does not mean making all data available to everyone, even internal users. Using patient data as an example, Lam noted that proper data governance is essential to protect confidentiality. He said: “There are specific drugs that only HIV-positive patients would take. Assuming proper classification of medical data, even knowing the medication that a patient is taking could reveal the specific condition a patient has.”
“I find data modernization and cloud to be mutually reinforcing in some way; both are critical to have in any organization… The modernization strategy will depend on the maturity of the business,” said Thilak, who sees the cloud as a linchpin to data democratization. “[The] cloud is the way for [data democratization]. There is no better way for any organization to unlock that value and drive decision-making through data without cloud and that is a no-brainer for anyone.”
To get to a place where organizations can benefit from their data, Rajasekharan says businesses should get their data estate modernized. Only then can they move to align applications to take advantage of data and establish a continuous feedback loop to make it work. “A lot of the things that we are doing today are informed by the journey that we went on,” he said, referring to Microsoft’s journey.
Paul Mah is the editor of DSAITrends. A former system administrator, programmer, and IT lecturer, he enjoys writing both code and prose. You can reach him at [email protected].
Image credit: iStockphoto/Carmian