Sanjay, in his career spanning over three decades, has managed key responsibilities across corporates such as Pertech Computers and Hewlett Packard, prior to joining Hitachi Vantara in 2017.

Digital Transformation(DX) is now a priority for businesses across APAC. At the heart of this transformation lies a critical enabler data. DataOps is needed to understand the meaning of data as well as the technologies that are applied to the data, so that data engineers can move, automate and transform the essential data that data consumers need. DataOps is a relatively new idea but it’s essential in today’s world where data is growing in volume and becoming more diverse, distributed and siloed than ever before. Businesses are looking to DataOps to efficiently get the right data, to the right place, at the right time in order to monetize their data and become a leader in today’s digital economy.

It has four components in the data stairway which are termed as store, enrich, activate and monetize, as the real value can be achieved with each step of the digital journey, but it all begins with data. These offerings enable our customers to:
Store: Store, manage and protect data at the lowest cost and at the right service levels across edge, private, hybrid, and multicloud solutions.
Enrich: Enrich data with metadata classification and cataloging to provide context for intelligent data management and governance.
Activate: Discover, integrate, and orchestrate enterprise data assets and leverage analytics to generate actionable insights for every enterprise interaction and application.
Monetize: Deliver outcomes that capture the full economic value of all the data inside our customers’enterprise and beyond.

In the end, it’s crucial our customers chose Hitachi Vantara a partner who will co-innovate with them to successfully deliver on their vision. This means always starting at the business outcome they are looking to drive, pairing this with the industry expertise only we have, and implementing integrated systems that maximize the value of data at each step of SEAM.

Internet Of Things Changing The Way The World Operates, Both In Terms Of Personal IoT & Industrial IoT
The Internet of Things(IoT) is a system of inter connected computing devices, digital machines, objects, sensors, actuators and network connectivity that enables these objects to transfer data over a network without requiring human to computer interaction. The Internet of Things(IoT)is a phrase that is becoming more and more common with estimates that by 2020, there will be more than 24 billion IoT devices.

•Appliances Will Do the Work for You: Things like building a grocery list; or that you could just place your order and pick it up exactly the way which you have wished for

• The Internet Is Becoming More of an Ecosystem: As more and more devices become smart and hook into a central hub that is your life, the Internet will become more of an ecosystem. For all these devices to share information and work efficiently, they are going to have to become more and more interconnected and figure out faster and better ways to communicate with one another

• Cloud Hosting will Explode: The only way that the Internet can become an efficient ecosystem is using cloud hosting, as it is impossible for the IoT to work without the cloud, because cloud allows your apps to follow you wherever you go.

• Healthcare will Improve: The very nature of IoT is well suited to healthcare as it collects and monitors data from different devices and departments. So it only makes sense that more doctors and hospitals will utilize this emerging technology to track vital statistics of their patients for more accurate diagnosis and treatment.

• Digital Twins are the next step in the world of IoT. In short, the digital twin is a virtual doppel ganger of the realworld things. In a software every where world, Digital Twin technology will help organizations bridge the divide between physical and digital data

• Blockchain will play a vital role in enhancing security, making transactions more seamless and creating efficiencies in the supply chain. Building trust and reducing cost would be the two keys in which it will operate. IoTs full potential will only be reached if security challenges are addressed. That requires a

combination of interoperability, education and good design

• 2018’s Smart City of IoT Projects will focus on improving people’s lives in the world’s biggest metropolises. This technology will help to streamline transportation by collecting massive amounts of data regarding traffic parking lots and public transport

• IoT projects will have the biggest influence on the retail industry which has already started using Machine Learning and IoT technology to improve their customer experience and increase their sales both online and instore.

Important Tools For Digital Transformation & How They Bring Change
Digital transformation is not just about providing a better customer experience through virtual shopping channels and agile customer service, integrated with social networks. An example that has already become popular is the customer who questions the seller within a physical store if he can discount certain merchandise because the customer has just seen on the internet that the competing store sells the products at a cheaper price. Digital transformation is changing the way in which the organization produces and delivers value to the market, but also to what the competition can do in that sense. Among the most used tools, the following have a major impact:

API Management: APIs are Internet protocols that enable the communication and exchange of data between different cloudbased tools. This allows independent developers or even large companies to integrate their solutions with those of other organizations, establish automated routines, new business ideals and especially more productivity for businesses.

Cloud Computing: Already widely adopted by most companies and the general public, especially with the use of SaaS applications (software sold as pay-as-you-go services), this technology is essential to promote more integration and teamwork.

Remote Access & Mobility: Wherever a collaborator customer vendor or partner is they can interact with your company by having a mobile device and an internet connection. This opens a huge range of possibilities that your business needs to explore.

Big Data: Perhaps the most complex digital transformation elements,it should not be overlooked. There are already Big Data solutions with Freemium and paid subscription models on the market.

Internet of Things: Also known as IoT(Internet of Things) it comprises several devices that have embedded technology, such as sensors, buttons, and others, that can connect in the cloud and transmit data and events.

Artificial Intelligence: Artificial Intelligence is the ability of a machine or software to develop human like thinking, including the ability to set standards, experiment perceive, and make decisions intelligently.

IT takes a community to build a Smart City through shared business, operational, and security intelligence that helps them deliver better services, run more efficiently and be safer places to live and work

Digital Transformation Helping Smart Cities & Industry 4.0
It takes a community to build a Smart City through shared business, operational, and security intelligence that helps them deliver better services run more efficiently and be safer places to live and work. Gathering information on buildings,course attendance and social interaction can ultimately be used to improve student experience and enhance learning. In the Hitachi Video Analytics(HVA) overview, HVA technology turns video cameras into smart city sensors that provide realworld insights for improved public safety, business intelligence, operational intelligence and greater ROI. Smart spaces and video intelligence combine the power of IoT, big data and analytics for better outcomes which support smarter operations for public safety & security, traffic & transit, airports & ports, campuses and retail. It is a one integrated view of activity, operations and safety issues with intelligence for realtime data and analysis which gather data from video cameras, IoT sensors, social media and other sources already in use. These tools are helping the industries to use business insights to match customer preferences from optimal product placement to more effective messaging for enhanced customer service. This on the other hand helps to utilize loss-prevention alerts, facial recognition, social media search and other tools. Data Analytics enables companies to enter the era of Industry 4.0, where manufacturers are using advanced analytics such as Hitachi’s Lumada IoT platform to extract value from industrial internet of things (IIoT) data. Manufacturers are turning to IoT technologies that combine manufacturing assets with embedded sensors, advanced analytics, artificial intelligence and cognitive computing to generate digital intelligence across the entire value stream. Lumada Applications for Industrial IoT helps to optimize asset and fleet performance through artificial intelligence, advanced analytics and data science to reduce unplanned downtime, which in turn improves performance and health diagnostics of assets and predict failures in advance. Manufacturing solutions reduce unplanned downtime with realtime fault detection & traceability and minimize product defects and operating costs, while increasing production throughput.

Cybersecurity Threats Of IoT & Ways To Counter Them
With the rapid adoption of mobile, cloud, big data and the internet of things(IoT), cybersecurity tools need to detect potential cyberattacks faster. To do this, you need to blend a large volume and variety of data from the applications network and server. This creates a big data problem that is hard to solve, because bringing data together from different formats, at scale is tough.

Cybersecurity Problems are Data Problems: Because traditional methods of handling cyber security involve custom scripting and integrating multiple data sources, it’s very time intensive to blend multiple data sources at scale. Data scientists often spend 80 percent of their time cleaning the data to get it ready to analyse, and only 20 percent of their time analysing the data.

Finding Anomalies is Time-Consuming & Urgent: Once you know what a security threat looks like, it’s easy to block. But how do you know what’s a threat in the first place? That’s hard, and that’s where data scientists come in to look for patterns. The average analyst takes 205 days to detect an attack due to the huge volume and variety of data to go through. And it’s not just big data, but all kinds of messy data from all kinds of sources, including log files, web access data, and more, that are difficult to blend. It takes time to clean and blend the data.