Data-driven analytics has become inevitable for businesses, which aim at customer satisfaction beyond their expectations. Combined with artificial intelligence, when operations are streamlined on the cloud, companies extract maximum benefit not only from the existing data but also by finding new sources. Hitachi Vantara, a data storage, analytics, and DataOps company, assists companies to find the zenith of data modernization and AI applications. Analytics Insight has engaged in an exclusive interview with George Philip, Director of Consulting Services, Hitachi Vantara.

1.Kindly brief us about the company, its specialization, and the services that your company offers.           

 In today's world, businesses can't sustain or remain relevant without digital experiences that are one step ahead of customer expectations. And this cannot be done without proper data intervention and analytics-enabled support, which form the backbone of digital operations. At Hitachi Vantara, we believe that data is a part of our DNA. We are among a handful of organizations globally that has data infrastructure, data products, as well as data & analytics services capabilities as a part of the core portfolios delivering significant business value to our customers. Our offerings include:

a) Highly scalable data storage & compute infrastructure – Forming the underpinning of modern cloud infrastructure

b) Lumada products: Object store-based data lake platform, AI-enabled data cataloging, DataOps suite of products, Lumada Analytics like MFI, Visualisation suite of products

c) Data & Analytics services – Rapid Data Modernisation to multi/hybrid Cloud Lake-houses, Artificial Intelligence/Machine Learning (AI/ML) implementations leveraging industry-oriented solution cores, Machine Learning operations (MLOps) accelerators for industrialized deployment across model management lifecycle.

With over 300 customers in India, our tailor-made, digital-driven solutions cater to the demands of most of the Fortune 500 and Global 2000 companies globally. Our customer-centric solutions are based on core problem identification and thus make for intuitive, easy-to-navigate business outcome-led approaches.

2.Tell us how your company is contributing to the IoT/AI/Big Data Analytics/Robotics/Self-Driving Vehicles/Cloud Computing industry of the nation and how the company is benefiting the clients 

Through our joint application modernization solutions and our ability to integrate across virtualized environments, customers are transforming their businesses quickly to improve both application availability and performance. Cloud acts as the biggest enabler of digital transformation and coupled with big data, artificial intelligence, and data modernization, businesses can derive true value out of their pre-existing data and map it for future developments. Hitachi Vantara offers its customers the opportunity to leverage their proven data modernization and AI solutions, frameworks, and accelerators, guided by experts, to reap real business benefits.

As the tech industry is advancing at a rapid pace today, it is not enough to have expertise in just public or private cloud networks. The hybrid cloud has been making the rounds as the technology of not only the present but also the future. Hitachi Vantara offers its customers the capabilities to move to a secure, scalable hybrid cloud with a mix of on-premises private cloud and third-party public cloud services. It not only makes for agile data applications that can be tailored to the customer's needs but also allows them to take control of their cloud infrastructure at every step. No company can achieve it single-handedly, especially in cloud computing. Hitachi Vantara collaborates with thousands of like-minded technology providers and partners across the globe to assist large, small, and mid-range customers with solutions to their data challenges.

3.What is the edge your company has over other players in the industry?

We are one of the very few companies globally that offer data infrastructure, data products, as well as data and analytics services capabilities to customers. We derive real-time value from pre-existing and current data & analytics services, which makes it easier for businesses to keep monitoring their activities and build efficiency in their processes.

4.How does your company's strategy facilitate the transformation of an enterprise?

Client perspectives are evolving, and so are we. We are experts in facilitating digital transformation for both traditional and upcoming businesses, regardless of the size of the enterprise. Our highly skilled and technologically enabled tech teams combined with our products and cloud-enabled services enable seamless collaboration. Digital transformation is the key. We focus on six areas when acting as transformation enablers, namely:

• Operational excellence: Improved efficiency with reduced complexity
• Business growth: Better earnings, better digital margins, and higher net income through digital channels
• Insight-led approaches: AI/ML and analytics in real-time with end-to-end tracking
• Collaborative effectiveness: Making people, culture, organizations, leaders, and teams more agile, responsive, and collaborative
• Partnered ecosystem: The power of digital transformation enabled through more flexible and responsive solutions
• Social innovations: Novel ideas cater to current social problems, including environmental impact generation 

5.How has been your journey in the analytics industry and what are some of the analytic solutions that you have worked on? 

At Hitachi Vantara, we believe that any business today requires data and analytics support to scale. Keeping this in mind, the company's journey in the analytics industry can be measured via real-time numbers and customer testimonials. We offer businesses an edge with solutions for efficiency, productivity, customer insights, and bottom-line impact. We have helped customers increase productivity by five percent, decrease total cost of ownership by as much as 30 percent and increase customer response rates by 20 percent, among other metrics.

Hitachi Vantara has over 4500 AI, analytics, and data patents for innovative technologies and applications that bring impactful business changes to our customers. We have also invested USD 2.9B in R&D Research towards co-creation for clients which continues to result in some of our greatest innovations.

In the past, we have worked with clients like Logan Aluminium to create a better digital footprint through Manufacturing Intelligence solutions with the objective to increase the client's competitive advantage while remaining cost-effective.  Another example would be our work with Maple Leaf Foods where we implemented our digital technologies to improve their operations, with features, such as AI-enabled digital barn tracking, smart cameras, and real-time alerts to supervisors.

6.What are some of the challenges faced by the industry today?

A major challenge faced by CIOs is that most of the IT vendors only address two or three of the problems faced by a business in their cloud journey. Choosing a vendor that provides them with end-to-end solutions without being biased towards a particular technology or solution will help make the transition smoother, quicker, and cost-efficient.

Due to the pandemic, the shift to the cloud was inevitable. But the cloud-cost paradox was a challenge that many enterprises encountered once they embraced their cloud journeys. Wasted expenditures of millions of dollars every year occur due to inadequate automation, lack of visibility across cloud accounts, and duplicate/idle resources from poor application architectural design. However, there is less awareness about how these unplanned costs can be addressed with flexible infrastructure choices, right workload shifts, and transparent processes. Strategic decisions based on FinOps principles will help avoid ungoverned on-demand consumption and unexpected management/operational costs. With the support of FinOps, organizations focus on cloud financial management through a combination of integrated systems, best practices, and the right expertise, which leads to a better assessment of cloud costs, smarter business decisions, and trade-offs.

The advent of big data heralded an exponential increase in real-time data generated by machines, humans, and complex business processes. Businesses now require complex data analytics for big data, which comes in real-time, leading to analytical applications becoming operational and mission critical. Data analytics has also become more complex as businesses need to derive value from structured and unstructured data. Today, enterprises struggle to manage this influx of data at scale. Companies that best address both data complexity and the kinds of data produced enjoy a strong competitive position in the market. Data complexity is also driven by the consumption needs of enterprises. At the same time, the legacy problems surrounding data quality and governance persist.

As AI/ML models evolve and move out of labs to actual production, their industrialization has become a major challenge for organizations. Model life cycle management through approaches like MLOPs is taking center stage in more mature organizations.

7.How can businesses efficiently extract the value from data, without increasing cost and complexity?

With data ingested at a high velocity and veracity with high throughput, the data quality problem has become manifold. The approach of ingesting data from all sources and then worrying about quality issues near consumption is now being re-evaluated.

The data lakes built over the last decade have become data swamps with untrustworthy data. These data complexity challenges are being mitigated by integrated cloud computing systems that provide cohesive services. Organizations today are migrating their legacy data structures to the cloud. The move is towards increased automation across the data pipelines with the capability to curate the data intelligently at scale. It can be done by bringing in AI-based systems that can curate, master, and qualify the data at a petabyte scale. Automating these data pipelines to have self-healing and governance capabilities can improve the quality and reduce complexity challenges in an enterprise. Heuristically majority of the data-heavy lifting goes into building the underlying data pipelines and getting the data to a shape where data scientists and analytics can consume it. Data Reliability Engineering principles being applied to the data and the pipelines through which it flows tend to provide higher data consumer confidence.

As organizations are trying to monetize their data, the emergence of approaches like Data mesh provides them with an alternative paradigm for treating data as a product moving away from the centralized data and consumption architectures of the past.

8.Kindly brief us about your role at Hitachi Vantara and your journey in this highly promising sector.

I am currently leading the HV Digital Insights practice based out of India. I have been working for more than 25 years in the Insights, Analytics & Data areas providing AI/ML, Big Data, and Cloud solutions deriving competitive business value for marquee customers across industries like Financial Services, Healthcare & Life Sciences, Retail & CPG, Telecom, Manufacturing.