Rigging Up Oil For The Data Economy
If data is the new currency, how ready are organizations to lead the data economy? Commissioned by Cloudera, a Harvard Business Review Analytic Services survey of 185 global executives across a wide range of industries finds that the vast majority (73%) believe that their data resources hold the key to creating business value—including 33% who gave it the highest possible rating: 10 out of 10 in terms of importance. More than half (51%) plan to leverage multiple cloud providers to achieve this strategy. Equally, nearly half (49%) of the companies plan to build machine learning and artificial intelligence (AI) capabilities over the next three years. At the same time, only one-third of the companies (34%) have an effective strategy for managing data in the cloud and more than two-thirds (69%) of the organizations are looking for a comprehensive data strategy to support their strategic goals.
Businessworld recently caught up with Vinod Ganesan, Country Manager-India, Cloudera, to understand more about why organizations need a new way to think about data and how to drive value and business outcomes using a modern data platform. Excerpts:
How do the results of the survey reflect your approach to the market?
The results of the study were very insightful, and we transmitted these insights to our engineering organization to build the Cloudera Data Platform. It satisfies the four key criteria we evolved on the basis of the results of the HBR Analytic Services study— an enterprise data platform that runs on multi-cloud and hybrid environments; handle multifunction workloads such as BI, analytics, machine learning, AI, IoT and more; ensure data security, protection, and governance; and is rooted in open source technologies to avoid vendor lock-in and ensure seamless interoperability between myriad computing ecosystems.
Considering that data is so important, what drives the move to cloud to run an enterprise data platform?
Data warehouses have to be scalable and scalability is like a moving target. This is where the cloud comes in. It can accommodate the data warehouse—along with all enterprise data ecosystems, both analytical and operational. Scaling up to tens of terabytes is quite affordable on cloud-based data platforms, compared to the capital expenditures incurred from the hardware and software licenses required to scale up an on-premises relational database management system, Hadoop, or a NoSQL database. Besides that, there are several other advantages of elastic resource management and ease of administration. Ultimately, the move to the cloud is part of modernization to achieve scale. Having said that it is important to note that the enterprise data platform has to work across on-premise, multi-cloud, and hybrid cloud environments.
Why do enterprises need a new approach to become data-driven? What does it entail?
The most valuable and transformative business use cases—IoT-enabled predictive maintenance, genomics research, real-time compliance monitoring—require multiple analytics workloads and data science tools and machine learning algorithms to run against the same diverse data sets. It’s how the most innovative enterprises unlock value from their data and compete in the data age.
But look at the reality. Analytic workloads are running independently—in silos—because even newer cloud data warehouses and data science tools were never designed to work together.
Data is spread across the enterprise—in data centres, public clouds, and at the Edge—and companies have no practical way to run analytics or apply machine learning algorithms to all their data. Add to that the need to make data secure and protected through a unified approach to data privacy, IP protection, and compliance.
So, what does the Cloudera platform offer?
Cloudera Data Platform (CDP) combines the best of Hortonworks’ and Cloudera’s technologies to deliver the industry’s first enterprise data cloud. CDP delivers powerful self-service analytics across hybrid and multi-cloud environments, along with sophisticated and granular security and governance policies that IT and data leaders demand.
How does the data platform approach mesh with digital transformation efforts?
Most organizations are currently in the phase of achieving digital transformation. Data management is a key area in digital transformation because it deals with data from the point of ingestion to its consumption in various modes. Consider also that every organization is embarking on being AI-driven, which requires a disciplined approach. For robust AI and ML, you need sound analytics and BI for which you need a modern big data platform. If you take each of these layers as a separate silo, you have lost the plot. Our platform brings it together in a unified way.
What’s the outlook for the Indian market? What have some of your customers been doing on the data management front?
BFSI and telco have always been at the forefront of using modern technology because of business need; they continue to lead and dominate in data strategy too. The added factor is that these are highly regulated industries and they need a higher posture in managing data security, governance, and compliance. Then comes the government sector with a lot of citizen-centric investments. As we move ahead, we are seeing an uptake in pharma and manufacturing.
A few examples from our Indian customers:
In the data-centric world, who should be the custodian of data?
Our practical experience suggests that technology is a great enabler. But the biggest challenge is culture. In my view, data-driven organizations cannot be built solely based on technology. I don’t believe in the concept of having one or a select group as custodians of data. Data cannot be locked in any system; it has to be democratized. Data should also be independent. The key element that gets neglected is the culture; to be data-driven, you need to have a fail fast mechanism till you perfect the culture. Without that, no amount of technology would help.
