LAS VEGAS: CrowdStrike announced innovations with Amazon Web Services (AWS), Intel, Meta, NVIDIA, and Salesforce to secure the future of enterprise AI. By embedding protection with the world’s AI leaders, CrowdStrike is uniting the ecosystem to innovate with AI, secure AI, and lead cybersecurity into the AI era with the CrowdStrike Falcon® platform.

AI is transforming every industry – but it also creates new attack surfaces. Models can be stolen, data poisoned, agents manipulated, and cloud workloads hijacked. The Falcon platform delivers the foundation for securing AI – protecting the environments and models where AI runs, preventing sensitive data from leaving endpoints and cloud workloads, uncovering shadow AI apps and risky integrations, and securing AI agents across the SaaS stack.

Securing AI With the World’s Leaders

CrowdStrike is extending Falcon protection across the AI ecosystem through innovations with the world’s AI leaders:

• AWS – Securing the full cloud AI lifecycle, from build to test, deployment, and runtime, with native integrations in Amazon SageMaker, Amazon Bedrock, and AWS Marketplace.
• Intel – Protecting data at the source with Falcon® Data Protection on Intel NPU technology, and with Dell’s trusted AI PCs, providing a stronger foundation for secure AI adoption.
• Meta – Launching CyberSOCEval, a new suite of benchmarks for evaluating how AI systems perform in real-world security operations.
• NVIDIA – Securing the full AI lifecycle for LLMs and Enterprise AI Factories – from build to runtime to posture management – with the Falcon platform and NVIDIA AI.
• Salesforce – Integrating Falcon® Shield into Salesforce Security Center and bringing Charlotte AI into Agentforce for Security to help customers protect their AI agent, workflows, and applications – uniting business and security teams on a foundation of trust.

“Securing AI is not just about technology – it’s about securing the full ecosystem where AI is built, deployed, and used,” said Daniel Bernard, chief business officer at CrowdStrike. “By embedding protection with the world’s AI leaders, we’re giving enterprises the confidence to adopt AI, innovate with AI, and secure AI, all while delivering revolutionary outcomes.”

CrowdStrike Secures the AI Ecosystem

AI doesn’t live in the network; it lives across the ecosystem where models are built in the cloud and AI Factories, where adoption happens on PCs and endpoints, and where autonomous agents take action. As AI transforms how work gets done, adversaries look for every weak point in the enterprise. By embedding unified protection with the companies driving the AI revolution, CrowdStrike is the cybersecurity center of the AI ecosystem.

To learn more about how CrowdStrike secures AI, visit here.

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Initial focus areas include:

• Sustainable and Secure AI Co-Development: The companies will develop sustainable and highly secure private AI solutions for organizations in regulated sectors such as financial services, insurance, defense, and the public sector. The companies will provide end-to-end solutions from infrastructure to business processes powered by AI applications for clients operating on private clouds.

• AI-Driven Innovation for IT Infrastructure & Customer Experience: The companies will pioneer the integration of Mistral AI technologies into NTT DATA’s customer experience platforms, beginning with agentic AI call center solutions in Europe and Asia Pacific. Joint projects could include co-development of LLMs for specific languages, which will further AI innovation tailored to local markets and specialized needs.

• Go-To-Market Expansion: NTT DATA and Mistral AI will jointly develop and execute regional go-to-market strategies tailored to the unique dynamics of countries, including France, Luxembourg, Spain, Singapore, and Australia. End-to-end AI services will range from use-case development and customization to implementation, support, and managed services. Dedicated sales teams will be assigned to address key client needs and priorities.

To drive innovation and implementation excellence, NTT DATA will establish a Mistral AI Center of Excellence staffed with subject matter experts and dedicated resources. In addition, Mistral AI will launch a technical enablement and certification program for NTT DATA personnel.

Abhijit Dubey, CEO and Chief AI Officer*, NTT DATA, Inc.

Arthur Mensch, CEO, Mistral AI.

Brochmann Laurent, Global Chief Digital Officer, Dennemeyer.

In another early effort, NTT DATA Luxembourg and Mistral AI will co-develop a sovereign platform in Luxembourg for clients in the regulated financial services and insurance industries.

Olivier Posty, Head of France and Luxembourg, NTT DATA.

* Additional role effective Sept. 1, 2025

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SAN FRANSISCO, CALIFIORNIA: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced at Snowflake’s annual user conference, Snowflake Summit 2025, that it has been named the 2025 Data Integration Data Cloud Product Partner of the Year award winner by Snowflake, the AI Data Cloud company.

Qlik was recognized for its achievements in helping joint customers accelerate trusted, AI-ready data pipelines on the Snowflake platform. Through innovations like native support for Snowflake-managed Iceberg tables and the introduction of the Qlik Open Lakehouse architecture, Qlik empowers enterprises to scale high-volume ingestion, optimize cost and performance, and unlock greater value from SAP and other enterprise data sources.

“This award is a reflection of how well-aligned Qlik and Snowflake are in delivering modern, trusted, and governed data engineering at scale,” said David Zember, Senior Vice President of Worldwide Channels and Alliances at Qlik. “We’re proud to help customers harness more value from their SAP and operational data through faster pipelines, Iceberg optimization, and SAP data products tailored for Snowflake environments. Together, we’re redefining what’s possible with AI-ready architecture.”

“The integration between Qlik and Snowflake has transformed how we manage and operationalize data,” said Michael Benassi, Vice President of Enterprise Analytics at United Federal Credit Union. “With near real-time ingestion and streamlined engineering pipelines, we’re able to scale insights across the business and support faster, more trusted AI initiatives.”

“The transformative results Qlik has achieved for our joint customers exemplify innovation in action,” said Kieran Kennedy, Global Leader for Data Cloud Product Partners, Snowflake. “Naming them as our 2025 Data Engineering Partner of the Year is not just recognition of their technical excellence, but of their vital role in shaping how modern enterprises harness the AI Data Cloud.”

Learn more about Qlik’s data engineering and Open Lakehouse solutions for Snowflake. Check out keynotes from Snowflake Summit 2025 live or on-demand here 

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LONDON, UK: The Royal Marsden NHS Foundation Trust, a world-leading specialist cancer center, has today announced a pioneering partnership with NTT DATA, a global leader in digital business and technology services, and CARPL.ai, a leading enterprise imaging artificial intelligence (AI) and machine learning operations (MLOps) platform. Together, they have designed and built an advanced AI-powered radiology analysis service for the development and evaluation of AI in medical imaging, designed to transform cancer research and, ultimately, improve patient outcomes.

AI’s potential to enhance the speed and accuracy of identifying imaging biomarkers has long been recognized. Funded by a three-year grant from the UK’s National Institute for Health and Care Research (NIHR), the service will be used for research at The Royal Marsden and the Institute of Cancer Research (ICR), including projects in collaboration with other research teams. This research initiative will focus on developing and evaluating AI algorithms to improve the accuracy of cancer evaluation, including sarcoma, lung, breast, brain, and prostate cancers. This will lead to faster response times, more accurate diagnoses, and better-targeted treatments.

The service runs on an MLOps clinical imaging platform, built and operated by NTT DATA. To enable this, NTT DATA developed a bespoke AI computing solution leveraging high-performance Dell servers and utilizing the latest GPU processing capacity orchestrated by the CARPL.ai platform, which helps test and manage AI algorithms and includes a large collection of radiology AI models.

NTT DATA is also providing specialist imaging AI consulting services, helping researchers at The Royal Marsden test and evaluate emerging AI tools in real clinical settings, while extracting maximum insight and value from both in-house and commercial algorithms.

“AI has immense potential to support clinicians in diagnosing and treating cancer earlier and more precisely,” said Professor Dow-Mu Koh, Professor in Functional Cancer Imaging and Consultant Radiologist in Functional Imaging at The Royal Marsden. “By working with NTT DATA and CARPL.ai, we’ve created a scalable research environment that allows us to explore the full potential of AI safely and in a way that could one day transform cancer diagnosis and treatment across the NHS.”

Minister of State for Health, Karin Smyth, said: “Our 10-Year Health Plan will modernize the NHS, replacing outdated systems with cutting-edge digital solutions. While this trial is in its early stages, it represents exactly the kind of collaboration between the NHS, industry, and academia that will help build a health service fit for the future. Early detection saves lives, and innovations like AI will transform how cancer is diagnosed and treated – helping patients receive faster and more effective care.”

Professor Mike Lewis, NIHR Scientific Director for Innovation, said: “Cancer is one of the biggest killers in the UK. That must change. This three-year grant will help researchers push the boundaries of AI-driven technology for cancer detection and diagnosis.

This AI-powered service represents the cutting edge of cancer research, and it is going to transform treatment, better support NHS staff, and ultimately change patients’ lives. It is another great example of how NIHR-funded and supported research will ensure the best care is there when patients need it.”

Tom Winstanley, Chief Technology Officer at NTT DATA UK & Ireland, commented: “This service is a great example of responsible innovation in practice, showing the ethical, secure use of AI in healthcare. We are very proud to support The Royal Marsden in pushing the boundaries of cancer research.”

Once the service is live, research teams at The Royal Marsden will be able to evaluate a range of AI models across several cancer types. These studies will generate critical insights into how AI can support clinical decision-making and shape future approaches to diagnosis and treatment. Through CARPL.ai’s centralized interface and built-in monitoring tools, the research teams will also be able to track model performance over time, enabling faster feedback loops between development and deployment – a crucial step towards clinical translation. NTT DATA will continue to work closely with The Royal Marsden to support this next phase of research, which will ultimately improve cancer care and patient outcomes.

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BENGALURU: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced an expanded set of capabilities coming soon in its Qlik Cloud Analytics solution — equipping enterprises with tools to detect anomalies, forecast complex trends, prepare data faster, and take immediate action through embedded decision workflows.

While organizations continue to invest heavily in AI and data, most still struggle to turn insight into impact. Dashboards pile up, but real-time execution remains elusive. Only 26% of enterprises have deployed AI at scale, and fewer still have embedded it into operational workflows. The problem isn’t access to static intelligence — it’s the ability to act on it. Dashboards aren’t decision engines, and predictive models alone won’t prevent risk or drive outcomes. What businesses need is intelligence that anticipates, explains, and enables action, without added tools, delays, or friction.

“Enterprises struggle making intelligence accessible and actionable for their business users,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “Too many systems deliver insights and answers after the fact. We’re building something different: a platform where AI detects what matters, surfaces it in context, and lets you act — all within the analytics environment itself.”

With these planned launches, Qlik will be introducing a new layer of intelligence across its platform — one that doesn’t just report what’s happening, but anticipates what’s next and enables action in the moment. Discovery agent, multivariate time series forecasting, write table, and table recipe work in concert to solve a singular problem: how to move from fragmented insight to seamless execution, at scale.

These launches, along with the renaming of Qlik AutoML to Qlik Predict^TM and Qlik Application Automation to Qlik Automate^TM, reflect a broader shift toward more intuitive, outcome-driven experiences across the Qlik platform. Each capability targets a critical enterprise bottleneck — from delayed awareness to inaccurate forecasting, data prep bottlenecks to disconnected workflows — delivering a cohesive solution that closes the gap between data and decisions.

• See what others miss before it’s too late — with the discovery agent. Executives no longer need to manually track business changes or sift through data. Discovery agent continuously scans performance across applications and datasets, automatically surfacing critical risks and opportunities before they intensify. Insights are delivered through a personalized feed that clarifies what’s happening, why it matters, and suggested next steps.
• Forecast reality, not just trends — with multivariate time series forecasting. Built into Qlik Predict (formerly AutoML), this capability moves beyond single-variable projections to model the full complexity of business conditions. By analyzing relationships across interdependent variables — like pricing, campaign activity, seasonality, and economic signals — it delivers sharper forecasts that reflect real-world dynamics. The result: more confident planning, faster scenario testing, and better decisions.
• Annotate and update data live — with a write table. Write table enables users to add context to data records directly in analytics tables, with instant sync across sessions and no reloads required. This capability enhances in-context data review and lays the groundwork for governed writeback into systems like SAP, Salesforce, and Snowflake — part of Qlik’s long-term vision for integrated, action-ready analytics.
• Prep data faster with no code — using a table recipe. Table recipe provides a streamlined, spreadsheet-like experience for preparing single-table datasets — no scripting or complex modeling required. Users can clean, convert, and format data with over 60 visual functions, seeing changes in real time. It empowers non-technical users to prep high-quality data quickly, accelerating the path to reliable insights.

“We’ve spent too much time reacting to what already happened — and not enough time getting ahead of what’s next,” said Olga Garagonich, Lead Manager, Data Visualisation, BT Group. “With these new capabilities in Qlik, we’ll be able to catch issues earlier, forecast more accurately, and take action — all without disconnected workflows or delays. That’s a game-changer for how we operate.”

Together, these capabilities transform Qlik from a system of insight into a system of execution — building the foundation for what comes next in enterprise AI: decision-making that’s not just intelligent, but contextual, automated, and embedded at the point of need.

Discovery agent, multivariate time series forecasting, write table, and table recipe will be available for private preview for select customers this year. General availability will begin rolling out in phases starting in summer 2025.

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ORLANDO, FL: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today introduced its new agentic experience at Qlik Connect^® 2025. The agentic experience will provide a single, conversational interface allowing users across the enterprise to interact naturally with data, using specialized AI agents to quickly uncover insights, drive faster decisions, and boost productivity, bringing new simplicity to complex data-driven workflows.

Qlik has consistently pushed forward the possibilities of data exploration, visualization, and analytics. At the heart of this continuous innovation is the Qlik engine—a unique technology that indexes relationships across data, enabling the discovery of unexpected connections. The agentic experience builds directly on this engine, expanding the ability of both users and agents to intuitively access these relationships, surface insights, and take action across diverse data.

The agentic experience will enable users to access insights and take action simply by engaging in natural language dialogue. Operating seamlessly across Qlik Cloud—including data integration, data quality, and analytics solutions—the experience removes friction, providing fast, intuitive visibility for smarter decisions and higher productivity.

At Qlik Connect, the company demonstrated how specialized AI agents will support users within this new experience:

• Introduced last year for unstructured data, Qlik Answers will bring together structured and unstructured data in a single natural language experience, delivering trusted answers and enabling automated actions.
• Revealed for the first time at the event, a discovery agent will proactively identify critical risks and opportunities across applications and datasets, presenting insights and recommended actions through a personalized feed.
• Demonstrated as a concept, a pipeline agent will allow users to describe desired business outcomes conversationally, prompting automated recommendations and the design of necessary data pipelines.

As enterprises face unpredictable market conditions and increasing pressure to make critical decisions rapidly, investments in AI have grown. With its agentic experience, Qlik is focused on helping customers turn data into timely, high-quality decisions and results. Qlik’s agentic experience is specifically designed to empower teams to accelerate both decisions and productivity in rapidly changing environments.

“This new agentic experience is about removing the distance between data, decisions, and outcomes,” said Mike Capone, CEO of Qlik. “People want a seamless, conversational way to engage with their data—one that fits naturally into their work and delivers clear, trusted answers in context. We’ve built this experience to reflect how business decisions are made.”

“There’s a growing demand for AI that does more than generate responses—enterprises want systems that can reason across complex data, explain their outputs, and drive action,” said Megha Kumar, Research Vice President, Worldwide Analytics & AI, IDC. “Qlik Answers combines structured and unstructured data with automation in a governed, explainable framework. It’s a strong example of how agentic AI can support real enterprise decision-making.”

“We’re under constant pressure to make faster, better decisions with data that’s scattered across the business,” said Yuzuru Fukuda, Corporate Executive Officer – Senior EVP, Enterprise Division CEO, Fujitsu. “The ability to ask a question and get a trusted, contextual answer—across structured reports, unstructured content, and automated workflows—is exactly the kind of capability we’ve been waiting for. It has the potential to remove a lot of friction from how decisions get made.”

The Qlik agentic experience is scheduled to begin rolling out this summer, starting with private previews. Through live demos and executive briefings, teams attending Qlik Connect can experience the agentic capabilities firsthand.

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ORLANDO, FL: Qlik^®, a global leader in data integration, data quality, analytics, and artificial intelligence, today announced the launch of Qlik Open Lakehouse, a fully managed Apache Iceberg solution built into Qlik Talend Cloud. Designed for enterprises under pressure to scale faster and spend less, Qlik Open Lakehouse delivers real-time ingestion, automated optimization, and multi-engine interoperability — without vendor lock-in or operational overhead.

This marks a major step forward in the evolution of modern data architectures. As organizations accelerate AI adoption, the cost and rigidity of traditional data warehouses have become unsustainable. Qlik Open Lakehouse offers a new path: a fully managed lakehouse architecture powered by Apache Iceberg that delivers 2.5x–5x faster query performance and up to 50% lower infrastructure costs, while maintaining full compatibility with the most widely used analytics and machine learning engines.

“Performance and cost should no longer be a tradeoff in modern data architectures,” said Mike Capone, CEO of Qlik. “With Qlik Open Lakehouse, enterprises gain real-time scale, full control over their data, and the freedom to choose the tools that work best for them. We built this to meet the demands of AI and analytics at enterprise scale — without compromise.”

Qlik Open Lakehouse is built from the ground up to meet the scale, flexibility, and performance demands of modern enterprises, without the tradeoffs. It combines real-time ingestion, intelligent optimization, and true ecosystem interoperability in a single, fully managed platform.

• Real-time ingestion at enterprise scale: Ingest millions of records per second from hundreds of sources — including cloud apps, SaaS, SAP, and mainframes — directly into Iceberg tables with low latency and high throughput.
• Intelligent Iceberg optimization, fully automated: Qlik’s always-on adaptive Iceberg optimizer handles compaction, clustering, and pruning automatically, delivering up to 5x faster queries and 50% lower storage costs — no tuning required.
• Open by design, interoperable by default: Access data in Iceberg tables using a variety of Iceberg-compatible engines, including Snowflake, Amazon Athena, Apache Spark, Trino, and SageMaker — without re-platforming or reprocessing.
• Your compute, your cloud, your rules: Runs natively in your AWS VPC with Bring Your Own Compute (BYOC), giving you full control over performance, security, and cost.
• One platform, end to end: From ingestion and transformation to governance, data quality, and FinOps visibility, Qlik provides a unified lakehouse experience — no patchwork, no handoffs.

“Enterprises are increasingly adopting lakehouse architectures to unify data across on-premises and cloud environments,” said Matt Aslett, Director of Research, Analytics and Data at ISG Software Research. “Qlik Open Lakehouse, which leverages open standards such as Apache Iceberg, is well-positioned to meet the growing demand for real-time data access and multi-engine interoperability, enabling enterprises to harness the full potential of their data for AI and analytics initiatives.”

As AI workloads demand faster access to broader, fresher datasets, open formats like Apache Iceberg are becoming the new foundation. Qlik Open Lakehouse responds to this shift by making it effortless to build and manage Iceberg-based architectures, without the need for custom code or pipeline babysitting. It also runs within the customer’s own AWS environment, ensuring data privacy, cost control, and full operational visibility.

“Qlik Open Lakehouse initiative is a significant development we’re keenly watching,” shared David Navarro, Data Domain Architect at Toyota Motor Europe. “Large corporations like ours urgently need interoperability between diverse business units and partners, each managing its own technology stack and data sovereignty. Apache Iceberg is emerging as the key to zero-copy data sharing across vendor-independent lakehouses, and Qlik’s commitment to delivering performance and control in these complex, dynamic landscapes is precisely what the industry requires.”

Qlik Open Lakehouse is available now in private preview and is scheduled to be generally available in July 2025. Private preview is limited — early access is encouraged for teams looking to modernize ahead of GA. To learn more and request early access, connect with us at Qlik Connect, May 14–17 in Orlando.

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INDIA: Hitachi Vantara, the data storage, infrastructure, and hybrid cloud management subsidiary of Hitachi, Ltd. (TSE: 6501), announced the Hitachi iQ M Series, the latest addition to the Hitachi iQ portfolio of AI-ready infrastructure solutions. This new solution provides a lower entry cost with built-in adaptability and scalability as customer needs evolve. Integrating accelerated computing platforms with robust networking, the Hitachi iQ M Series combines Hitachi Vantara Virtual Storage Platform One (VSP One) storage, integrated file system choices, and optional NVIDIA AI Enterprise software into a scalable, adaptable, cost-effective AI infrastructure solution.

The rise of generative AI and the explosion in data processing power are pushing the pace of change. As more businesses adopt AI, the rapid increase in training costs and data management presents significant challenges. The Hitachi iQ M Series allows for a choice of NVIDIA accelerating computing platforms to select the most suitable GPU for specific workloads to ensure optimal performance across different AI applications. The solution allows for the scaling of compute and storage independently with the flexibility to adapt to diverse and fluctuating data sizes, data types, and workloads, meaning businesses can allocate resources efficiently, scaling compute or storage as needed rather than overprovisioning, and reducing unnecessary expenses.

Additionally, Hitachi iQ is integrating the NVIDIA AI Data Platform reference design, created to power the era of enterprise agentic AI. Using the design, Hitachi Vantara will integrate its premier enterprise-grade storage with NVIDIA’s accelerated computing, networking, and AI software to enable AI agents with near real-time business insights. This ensures that Hitachi Vantara customers will benefit from the highest standard for performance and reliability, seamlessly powering their most critical AI applications and transforming their data into actionable insights. Through its continued collaboration with NVIDIA, Hitachi Vantara will continue to innovate its AI-ready infrastructure, reshaping how organizations manage and use data, and closing the gap between AI agents and business knowledge.

“We’re on a mission to help customers from all industries harness the power of AI regardless of the market they’re in,” said Jason Hardy, chief technology officer for artificial intelligence at Hitachi Vantara. “With the expansion of computing power from Hitachi iQ M Series and the high performance and reliability standards inherent in the NVIDIA AI Data Platform, we have created a unique opportunity for businesses to innovate, revamp user experiences, streamline operations, and optimize cost. This enables businesses to capitalize on AI without overburdening their teams or their bottom line.”

As a part of the Hitachi iQ portfolio, the M Series features flexible configurations using NVIDIA accelerated computing and a choice of a high-performance file system or a global namespace file system. There is also an optional object storage repository available within the Hitachi iQ portfolio. As a result, the M Series can handle the various data types, sizes, and workload demands, making it ideal for businesses operating in dynamic and data-intensive environments.

“Enterprises generate and store vast amounts of data, much of it unstructured and inaccessible to modern AI-driven applications,” said Bob Pette, vice president of enterprise platforms at NVIDIA. “With the AI Data Platform reference design, stored data is accessible in real-time on Hitachi iQ, giving applications access to full knowledge of the business and providing invaluable insights that strategically accelerate AI initiatives.”

Hitachi iQ Powered by Hammerspace and VSP One

Additionally, to bolster the data orchestration power of Hitachi iQ, Hitachi Vantara has entered into a strategic resell agreement with Hammerspace, a fast-growing software company that is radically changing how data is used and preserved. Through the agreement, Hitachi Vantara has integrated Hammerspace software with the VSP One storage platform, expanding Hitachi iQ’s capabilities to address different data management requirements for dataset creation, processing, governance, and protection. The joint VSP One and Hammerspace solution ensures that distributed data is easily and transparently accessible from anywhere for GenAI workloads. As a result, Hitachi iQ represents a complete infrastructure solution for AI, GenAI, analytics, and data lake environments across a range of industry-specific use cases.

The Hitachi iQ portfolio of AI-ready infrastructure, solutions, and services is among the most comprehensive, end-to-end AI enablement tools available today. The portfolio includes an AI Discovery Service designed to help customers identify the most valuable AI use cases, assess their data readiness, determine ROI, and create a strategic roadmap for successful AI implementation.

Video: https://www.hitachivantara.com/en-us/video/evolving-ai-with-hitachi-presented-by-hitachi-vantara

Blog: Unleashing AI’s Full Potential: Hitachi Vantara to Help Solve the Data Challenge Using NVIDIA AI

Blog: Unleash the Power of Your AI Initiative with Hitachi iQ

Blog: Discovering the Potential of Your AI Initiatives and Applications to Achieve GenAI Success

For more information on Hitachi iQ, please visit:

https://www.hitachivantara.com/en-us/solutions/ai-analytics/hitachi-iq

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BENGALURU: UST, a leading technology and digital transformation solutions company, has announced the inauguration of a new office in Pune, Maharashtra, further strengthening its India presence. Through this expansion, UST plans to create around 3500-6000 job opportunities in the next 3-5 years in Pune.  Located in Balewadi’s EQ Smartworks establishment, this new facility spans over 80,000 sq. ft and accommodates over 1000 seats, complementing the facility at Sai Radhe Complex in Pune.

The new Pune office space was inaugurated by Krishna Sudheendra, Chief Executive Officer, of UST, in the presence of Alexander Varghese, Chief Operating Officer; Sunil Balakrishnan, Chief Values Officer; Ramprasad Santhanagopalan, President, of UST Product Engineering and Pune Center Head; Kishore Krishna, Vice President & Global Head Talent Acquisition; Smitha Suryaprakash, Vice President, Design & Experience Practice; Sheffi Anwar, General Manager; and Hari Krishnan Mohankumar, Senior Director Workplace Management & Operations, and other senior leaders and associates at UST.

With over 2000 employees, UST’s Pune Center of Excellence is focused on driving innovation and accelerating growth by leveraging deep expertise in data science, data engineering, design, product engineering, and digital applications. Serving leading global enterprises across industries such as fintech, healthcare & life sciences, retail & e-commerce, manufacturing, and automotive, the Pune center plays a key role in shaping digital transformation for UST’s global clients.

On this occasion, Alexander Varghese, Chief Operating Officer, UST, said, “We are excited to inaugurate our new office space in Pune, marking a significant milestone in our continued growth in India. Through these strategic expansions, we are planning to scale our operations significantly, aligning with business needs and market opportunities in digital transformation. Our focus is on building a strong talent base, business consulting pipeline, strategic partnerships, and expanding infrastructure to support our growing teams in AI, Design, and Engineering.”

Ramprasad Santhanagopalan, President, of UST Product Engineering and Pune Center Head, said, “Pune is a strategic and fast-growing technology hub of India, this new office represents a significant investment in UST’s growth in the region.  Our investments in AI, advanced design, and cutting-edge engineering will strengthen our capabilities, ensuring that the Pune Center remains a hub for innovation and digital excellence. With our team’s strong domain knowledge expertise, we are confident in our ability to lead large-scale digital transformation programs for our global enterprise clients and remain at the forefront of innovation.”

For the next three years, UST is dedicated to aiming to attain consistent growth in terms of both seating capacity and headcount across India offices.  The company intends to greatly expand its operations over the next three to five years, in line with business requirements and market opportunities in digital transformation and AI. UST concentrated on creating a strong pipeline for business consulting, cultivating a large talent pool, and establishing strategic alliances.

UST has consistently expanded its footprint across India, solidifying its position as a global leader in digital transformation and technology services. Last year UST opened a second office in Bengaluru along with a Design Experience Centre. The company laid the foundation for its second-owned campus in Kochi, Kerala, with plans to create 3,000 jobs over the next five years in Kochi, demonstrating its commitment to growth and investment in the region. In 2023, the company also inaugurated a state-of-the-art office at the International Tech Park in Hyderabad, dedicated to innovative research and development in emerging technologies.

The California, US-headquartered firm, UST founded in 1999 with its India headquarters in Thiruvananthapuram, has significantly expanded its footprint across the country, with offices in key locations including Bengaluru, Thiruvananthapuram, Hyderabad, Kochi, Pune, Mumbai, Chennai, Coimbatore, Delhi NCR, Ahmedabad, Hosur and employs over 20,000 employees in India.

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The role of data analytics in healthcare is revolutionizing how patient care is delivered and how healthcare organizations operate. By harnessing the power of data, providers can improve patient outcomes, reduce costs, and create a more efficient healthcare system. From personalized treatments to predictive models and business opportunities in analytics tools, the future of healthcare is undeniably data-driven. For those in the healthcare space, embracing analytics not only improves patient care but also opens doors to new avenues of growth and innovation.

In the rapidly evolving landscape of healthcare, the integration of data analytics is becoming indispensable. As the industry grapples with increasing patient demands, escalating costs, and regulatory complexities, the transformative power of data analytics offers a promising solution. By leveraging advanced analytics techniques, healthcare providers can enhance patient care, streamline operations, and reduce inefficiencies.

At its core, data analytics in healthcare refers to the use of quantitative and qualitative data to extract actionable insights. These insights can range from improving patient outcomes to optimizing administrative workflows. With healthcare systems increasingly digitized, data from a myriad of sources—patient records, wearable devices, diagnostic tools, and hospital management systems—can now be analyzed to uncover patterns, predict trends, and inform decision-making.

 Benefits of Data Analytics in Healthcare:

• Improved Patient Outcomes: Data analytics enables healthcare professionals to make evidence-based decisions, resulting in more accurate diagnoses, personalized treatments, and proactive patient care. Predictive analytics can identify patients at risk for chronic conditions, enabling earlier intervention.
• Enhanced Operational Efficiency: With the massive influx of patient data, healthcare institutions are utilizing data analytics to streamline their operations. By analyzing patient flow, resource utilization, and staff performance, hospitals can optimize scheduling, reduce waiting times, and improve bed management.
• Cost Reduction: Data-driven insights can significantly cut down operational inefficiencies, reducing unnecessary testing and treatments, and improving overall cost management. By identifying patterns in resource consumption, analytics helps hospitals avoid wasteful practices and make cost-effective decisions.
• Personalized Patient Care: Through data mining and machine learning, healthcare providers can analyze individual patient histories and genetic profiles to deliver more personalized care plans. This precision medicine approach ensures that treatments are tailored to the specific needs of each patient, increasing the likelihood of successful outcomes.

1. Predictive Healthcare: One of the most exciting applications of data analytics in healthcare is predictive modelling, which anticipates patient needs before they arise. This proactive approach helps in preventing diseases, reducing readmission rates, and improving the overall quality of life for patients.

Example: The use of predictive analytics in chronic disease management, such as for diabetes, allows doctors to anticipate complications and intervene earlier, which has been shown to reduce hospital readmission rates by up to 30%.

Tools and Techniques in Healthcare Data Analytics:

• Electronic Health Records (EHRs): EHR systems store comprehensive patient data, which can then be analyzed to track patient health trends, identify early signs of disease, and improve coordination among healthcare providers. Tools like Epic Systems and Cerner are widely used to consolidate patient data for easier analysis.
• Big Data Analytics Platforms: Healthcare organizations use platforms like Hadoop and Apache Spark to manage vast amounts of unstructured data, which can be mined for valuable insights. These platforms help analyze patient records, medical imaging, and even genomic data at scale.
• Predictive Analytics Tools: Tools like SAS Analytics, IBM SPSS, and Tableau empower healthcare professionals to create predictive models and visualize data, making it easier to identify trends, predict patient outcomes, and optimize resources.
• Natural Language Processing (NLP): NLP tools, such as Google Cloud Natural Language API or Clarifai, analyze and interpret the vast amounts of unstructured text data in medical records. This enables healthcare providers to extract useful information from clinical notes, improving the decision-making process.
• Wearable Devices and IoT: Wearables, such as Fitbit, Apple Watch, and Garmin, along with IoT (Internet of Things) devices in hospitals, continuously collect patient data like heart rate, blood pressure, and glucose levels. This data is integrated into analytics platforms to provide real-time insights into patient health.

Implementation of Data Analytics in Healthcare:

1. Focus on Data Quality: Ensure that the data being used for analysis is accurate, complete, and up-to-date. Poor data quality can lead to misleading results and ineffective interventions. Implementing robust data validation processes is essential.
2. Interdisciplinary Collaboration: The integration of data analytics into healthcare requires close collaboration between data scientists, healthcare providers, and IT teams. Establishing cross-functional teams ensures that the insights generated are actionable and aligned with clinical goals.
3. Prioritize Patient Privacy: With the vast amounts of sensitive data involved, maintaining patient privacy and adhering to healthcare regulations like HIPAA is paramount. Use encryption, access controls, and secure data-sharing protocols to protect patient confidentiality.
4. Iterative Approach: Start small with pilot projects that address specific issues, such as improving ER efficiency or predicting readmission risks. Once initial results are promising, scale the analytics initiatives across the organization for broader impact.

Business Opportunities in Healthcare Analytics:

• Healthcare Analytics Software Companies: As demand for healthcare data solutions rises, there is a growing business opportunity in developing and selling analytics software tailored to the healthcare industry. Companies can provide platforms for data management, visualization, and predictive modeling.
• Data Consulting Firms: Healthcare organizations often lack in-house expertise in data analytics. Consultants can capitalize on this by offering services to help healthcare providers implement data-driven solutions, such as improving patient care or reducing costs.
• Personalized Healthcare Services: Entrepreneurs can tap into the growing market for personalized medicine by using data analytics to offer customized health plans, predictive insights, and even targeted treatments based on a patient’s genetic makeup.
• Predictive Maintenance for Medical Equipment: Predictive analytics isn’t just for patient care—it can also be applied to hospital infrastructure. By analyzing equipment performance data, hospitals can predict when devices are likely to fail, enabling timely maintenance and reducing downtime.
• Health Data Security Solutions: As healthcare organizations increasingly rely on data analytics, the need for robust data security solutions will continue to grow. Businesses offering cybersecurity solutions for healthcare data can capitalize on this trend.

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