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In a wide ranging conversation about tech and culture – covering topics from data analytics to the importance of diversity – Kandiah spoke with me about Hitachi Vantara’s current and future strategy.

Among the topics we covered:

Hitachi Vantara’s recent acquisition of Global Logic, a San Jose-based provider of digital engineering services.

Kandiah become CEO relatively recently, in July 2023; he spoke about his experience so far.

The struggle that many companies have in finding success with data analytics, and some examples of companies that have succeeded, with a view toward the social good.

What it means to “skate where the puck is going” in the the tech market, and the trend toward customers that seek holistic solutions and partnerships, not just products.

How the pandemic has driven an ever increasing focus on maximizing the value of data analytics.

How his experience as an immigrant to the US has shaped his management philosophy.

His own struggles with Imposter Syndrome, and how he uses this to avoid complacency.

His deep commitment to diversity and inclusion as essential element of success in business.

Edited highlights from the interview:

Hitachi just announced it is acquiring GlobalLogic. The company is based in San Jose, they provide digital engineering services. What was your strategy in acquiring GlobalLogic?

Software is eating the world. It’s a software play in many ways. It certainly enables an IoT play, the edge play, the data, data-driven play, if you will.

But in essence, for industrial companies and enterprise organizations to compete, increasingly, software is becoming a core requirement for them. And it’s true for us as Hitachi, as an industrial company, but it’s also true for our clients. And as we were looking for a set of capabilities that could enhance and accelerate and catalyze us as well as our clients, we identified GlobalLogic.

We’re very excited with their core capability, their delivery, the extensive delivery capability, their software engineering capabilities, and most importantly, their ability to work closely with clients to identify new sources of revenue and then build the software that enables them to go and capture it.

The importance of data and maximizing the value of data has really come to the forefront these days, that a lot of companies have gathered a lot of data, oceans of data. I think sometimes they don’t know how to get the most from it. What about some success stories? What’s a company that really has succeeded with data, along the lines of powering social good or an environmental cause?

And so I’ll echo your point, and I think one of the things that we’ve gotten really excited about is the concept of data-driven outcomes. By company, by industry, by segment. But the reality, and you nailed it, is data is growing exponentially and the ability, outside of a select few companies that you keep hearing about all the time, good deeds, bad deeds, you name it, is extremely low.

So talking talking about data and powering good, you know the work that we’re doing with the Rainforest Connection around deforestation is something that is truly both meaningful, powerful and close to my heart.

We are working with them to identify, to predict…a deforestation, illegal deforestation event using data, using sound and to be able to rapidly respond to someone that may be preparing to cut down a forest somewhere in the world and get the law enforcement there ahead of time, even before the event occurs. And I think that’s just a small example of how you could use data to power good and truly you know change some of the environmental elements that we have been talking about.

You’ve talked about helping Hitachi Vantara “skate where the puck is going.” I think it’s really tough to figure out where things are going in today’s marketplace. What does that mean to you to skate where the puck is going in a strategic sense?

You know, in today’s world, especially with a little bit of light at the end of the tunnel around the pandemic, we’re living in a world that business schools do not have models for, right? in many cases, people are coming along who have great strategies, but have never dealt with this type of a situation.

So it is super important for us to listen to our customers, listen to market signals and derive the point of where the puck is going from that process. So it becomes much more client-intensive and lot more listening intensive.

One thing we do see is this preponderance of data, data really exploding and the pandemic has only accelerated that. The second thing is the movement to the cloud; the third is the coming together of both the infrastructure and the products and the digitization of them.

We see our clients sort of either in trying to catch up with data and how to utilize data, in some cases able to make some meaningful sense of data and in very few cases capable of deriving new value from dat. And we think as a data company, based on where we come from, from storage, we have the opportunity to help our clients on that journey, and that’s sort of where we expect the puck to go, and that’s where we want to play.

I know that part of your strategy and your life has been shaped by the experience of being an immigrant, remarkably, when you are young, your family was forced to immigrate to the US to flee a civil war. How has it influenced your experience, being an immigrant to the US?

 You know it’s funny, right, When I first came here, you know we were like you know… The only thing we knew about the US was you know either Charlie’s Angels or Sesame Street, right, so you know and I’m sure you can relate…

So you expect that when you arrive here right and you end up an immigrant, you know you have a couple of bucks in your pocket and you’re in a neighborhood that you can afford, right? It is what it is.

So being the land of opportunity really comes to the fore, and especially going through the political season of last year and so on and so forth. I strongly believe that this is the country that gave me the opportunity to explore, push, learn, understand.

If you were willing to work hard, then we come from a family that works hard, a country of people that works really hard for what you want, this country gave me the opportunities. I had a really strong foundation with my parents you know, father being a military officer from the army, my mother being a Montessori teacher. And being an only child right, so there was a lot of focus on me – and you know there was some disappointment that I’d never turned into a doctor or lawyer or an engineer…

My dad has always been one of these people about, “Listen, listen, listen, listen.” Always listen, because you need to find your own voice, but listen first. And so this concept of ‘you have two ears and one mouth, so you have to listen twice as much as you speak,’ was something that was ingrained in me from the early days, and it’s been a part of the journey, and it’s been a hugely helpful part of the journey.

To first identify who I am and what I bring to the table, then to open up and speak about it. And then as I have had the opportunity to lead teams and companies at this point, to ensure that I’m giving my team the opportunity to voice their opinion, pull it out, understand, connect the dots together, and then set the path forward. So it’s been fantastic – though the beginning wasn’t that great, getting to where we have been has been great.

To wrap up our conversation, I think it’s important to talk about this idea that you’ve stressed, which is leading with inclusion. What does that mean to you, and how does that shape your approach?

First of all, we can all do a lot more around inclusion. I think that it’s a shame that we’ve continued to have to talk about diversity and inclusion on an ongoing basis. But that said, I have found that diverse and inclusive teams tend to be far more effective and successful than sort of the typical executive committee or board room that you would see. Because I think that there’s a sense of balance between market economics, how aggressive do you want to be, the environment, safety, security, privacy…

There’s a lot of things that matter in today’s world that didn’t in the past. And the ability to balance all of that in the context of a P&L that you operate is a critical, critical thing that a chief executive needs to do. And I think to do that you need a diverse team and you need an inclusive team. The diversity of thought that that team brings to the table helps you balance the approach and the strategy that you set for your company, and it factors into how you navigate. Because I think intelligence and empathy are both important, and you don’t always find one person with both.

And again, back to this notion of inclusion, I think however you cut it, I think the more diverse your team is, the more inclusive your leadership style is, the better it is for your business, and so that’s why I’ve been stressing inclusion.

I think one of the best things about our current era is for all its problems, is that that idea [of diversity] is very much on the rise, and I think companies will benefit as they embrace that.

And I think, Jim, that the pandemic actually has accelerated the opportunity for us to bring people who we may not have had access to, who may have gone off to raise their child, or whatever it may be, and was not quite sure how to get back to work.

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Exclusive Interaction With Sushant Gupta, Founder & Ceo, Sg Analytics

The massive amounts of data generated by modern organisations are influencing organisations to adapt to data-centric research where ready-made data is available for analytics and harnessing business intelligence. Understanding the right data and tracking the effectiveness of processes and strategies, offers relevant insights across marketing, consumer, sales, and operations, and supply chain management. In an exclusive interview with Analytics Insight, Sushant Gupta, Founder & CEO of SG Analytics, shares how competitive intelligence, in accordance with machine learning-based automated classification models are key to empower crucial business decisions. Below are the excerpts from the interview-  

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

SG Analytics, founded by me in 2007 is a leading provider of data-centric research and contextual analytics services to Fortune 500 companies across the globe. Headquartered in Pune, the company has presence across 7 locations in India, the USA, UK & Switzerland. At SG Analytics, we understand our clients’ businesses. We offer research and analytics services that deliver holistic rather than just functional solutions. Our contextual understanding of our clients’ businesses, data and sector expertise helps us provide actionable, ‘differentiated’ insights to our clients which help them scale faster and develop new products and bring them to the market faster.  

With what mission and objectives, the company was set up? 

SG Analytics was founded with the overarching vision to enable positive change by collaborating with its customers, employees and the society. Quality is at the centre of our service focus and we continuously strive to align all our individual efforts to deliver services to our clients across sectors and help them scale and grow by providing them data-centric research and contextual analytics solutions.  

Brief us about your role in the company and your contributions toward the industry. 

As the Founder & CEO of SG Analytics, I have tried to create a front leading, global company that cares for its people, clients and society. Over time, SGA has grown from being an investment research focused company to a full-stack, data centric research and contextual analytics company serving its clients across the spectrum. In SG Analytics, I have created a company that is invested in the well-being and growth of its people and its clients; some of the oldest employees of SGA are still with the company having risen to strategic senior leadership positions. At the centre of SGA’s DNA lies the continued focus on quality and personalized service extended towards SG Analytics’ diverse, global clientele, several of whom have been long time clients of the company, now inextricably sewn into SGA’s growth story. Being a socially conscious entrepreneur, I have been one of the early investors in Aavishkaar, the world’s first rural venture capital fund that pledged to harness the entrepreneurial spirit at the bottom of the pyramid to create inclusive economic development. In SGA, we have created a socially responsible company that is at the forefront of positively impacting the society through several CSR initiatives. Only recently, I, along with the company, have launched the ‘Ek Nishchay’ initiative that aims to touch the lives of nearly 35,000 Covid-19 affected individuals in Pune and surrounding villages by providing them Ration kits and medicines. (You can find out more about Ek Nishchay here:  

Kindly share your point of view on the current scenario of the Big Data Analytics and its future.  Kindly mention some of the major challenges the company has faced till now.

SGA was started in one of the rooms in my house in Pune. The founding story of SGA has been a testament to the persistence and focus it took to grow the company against several odds. Soon after the company started, the financial crisis hit, and the company’s survival was threatened. However, SG Analytics has managed to grow from humble beginnings to being a global brand owing to its relentless focus on providing differentiated services to its valuable clients. With no external investment and growth driven purely from its cash flow, we are now proud to have created a company that attracts the best of the talent as well as satisfies the requirements of its very discerning clients.  

What’s your growth plan for the next 12 months?

We plan to move deeper into the Technology & Healthcare sector, Data Governance, ESG and Productization; we plan to further grow in the US & UK and develop a talent pool that is global in nature.  

What have been the most significant challenges that you have faced at the forefront of analytics?

Some of the more significant challenges we have faced as a company at the forefront of Analytics include: 1) Getting access to the right data and the complete analytics exercise to generate insights in the shortest possible time remains the biggest challenge. 2) Making sure that the business insights are getting delivered and consumed by the business stakeholders in a simple and easy to understand manner. 3) The third biggest challenge is a shortage of talent. Experienced data engineers and data scientists who are proficient in data engineering and Machine Learning, who can quickly understand the business context are not easily found.  

Please share some major achievements of SG Analytics under your leadership

Strong financial results coupled with a strong set of values: While tangible growth is a great measure of success, and in that we have witnessed the company growing steadily over the years (now close to 18 mn USD in revenue). I would also like to attribute SGA’s success to the way we have grown as a company in terms of identifying, sustaining and developing a strong set of values. Our values are modern and inclusive in nature with no differentiation between people, along with emphasis on both commercial and ethical personal growth.   Continuous innovation and development of related set of services: As part of our growth story, despite facing some limitations and odds, SG Analytics has continuously innovated through the years – from being an investment research company to integrating research and analytics as part of our offering, we have moved up the value chain and are being recognized as a preferred partner of choice for our clients who comprise some of the world’s most respected names in the Financial services, Technology and Media & Entertainment sectors.   Sharing our success with our people: Our profits and success are shared with our employees. In fact the entire ownership of SG Analytics resides within the company, with many of the employees being co-owners including those who started as freshers and are now in senior positions, as well as dividend earners.   High degree of social awareness and impact:

Why Does Your Company Need To Use Analytics For Higher Organizational Success?

Understanding the importance of workforce analytics powering Business Growth.

Imagine, you are head of a department in your company. It is obvious that the department has other members too of various talents and capabilities. So how would you assign them job roles and responsibilities that match with their talents and abilities? How do you identify the problem areas, monitor employee performance, handle operations, find out the best performing individuals and overachievers? What methods would you use to connect with your peers? What are the steps you shall take to ensure employee retention and job satisfaction? How would you know if the deadlines are met? What are the brand objectives? How can the company show that it cares for its employees, especially during COVID-19 pandemic times? How will you deal and manage all these things? The good news is that analytics can be now be used to manage people. This fits perfectly with companies that consider their employees as their best resource even when they are equipped with state-of-the-art technologies. Workforce analytics can help leaders and authorities to make informed data-based decisions at a quicker pace than relying on mere intuitions. If the pandemic has highlighted anything, it is how important are employees’ healthcare both physically and mentally, along with an emphasis on their safety and engagement. This has proved an opportunity for the HR managers to showcase that they are concerned about the well-being of the employees and take measures to ensure continuity of business activities. This is important for the companies, too, as a healthy employee who can communicate effectively with his peers, subordinates, and superiors can contribute to business success in the long run. Surprisingly, people believe that workforce analytics can be performed only if the data amassed is perfect. Also, many organizations focus on data instead of the problem source in business. Leaders must realize that the data they require has a higher likelihood to be present already. They must prioritize identifying the problem points and brand objectives before hiring an expert, i.e., data analyst and data scientist , to deal with the issues or design a model that does. For this, leaders need to connect with the strategy teams too. Apart from that, they can conduct surveys (large organization) or group meetings (small scale organizations) periodically to discover the potential areas of improvement. Besides, they can use dashboards to visualize the data insights and monitor data quality regularly. It is also equally vital to note the participation rates as it could signal overload if participation decreases. The aforementioned things are needed to maintain engagement by understanding employee needs and satisfaction levels, even in the COVID-19 lockdown periods. Workforce analytics will also help in determining and fixing compensation rates for employees who are over-performing but have not yet been acknowledged. It can be used to establish performance benchmarks for the employees, and track the same to measure their future potential so that support can be provided. In case, training and skill gaps are found, training sessions can be organized. At the same time, high-performing employees can be mapped as per the requirements and performance specifications of other roles in order to facilitate succession planning. Analytics can further help to scan for future organizational needs so that recruitment will satisfy talent requirements. In addition, it is also resourceful in locating areas where efficiency can be improved with automation, which can boost employee satisfaction too. In gist, workforce analytics goes a long way as an instrumental tool that can lead a company to better organizational success, stakeholder and employee management, and retention with the ability to empower a leader to make an informed decision that benefits everyone.

Top 10 Big Data Analytics Linkedin Groups

LinkedIn is the chief place for enterprise innovation experts to accumulate, connect with each other, share thoughts, and network with other people. If you are a specialist who works in the data science or predictive analytics space, or you’re simply searching for extra insights into what the smartest in the business are discussing, LinkedIn professional groups are an extraordinary place to begin LinkedIn has turned into the go to place for experts to look for occupation, connect with their friends and to share their perspectives on a specific theme. In this article, we go through the absolute most well-known LinkedIn groups that are devoted to the field of data science and big data that working experts, students etc.  

The group was established in 2012 and seen as probably the greatest group in the platform committed solely for the discourse, trading thoughts and giving input on issues identified with big data and analytics. The number of members in the group go to 3 lakhs plus members. Some of the topics of discussion in this group are about blockchain, artificial intelligence, machine learning, etc.  

Advanced Analytics and Data Science gives an asset to the individuals who need to find out about and utilize these abilities and meet other individuals associated with predictive analytics, machine learning, statistics and big data. Offer your thoughts with different experts and figure out how to apply the most recent tools and techniques to solve your most significant business challenges.  

The group means to unite stakeholder communities across industry, companies, academia, and government segments with interests in big data and visualisation methods, innovations, and its applications. People who are Hadoop designers, data scientists, business experts, analysts and programmers, CIO, CMO, CDO etc. can gain a lot of insights from this group. Discussions are around Hadoop, data warehousing, cloud, unified data architects, digital marketing, business intelligence and visualization.

This present group’s motivation is to assemble every one of the data science, big data, AI, machine learning and business insight experts in the United States and abroad to share proficient experience and consulting tips. chúng tôi is building the world’s biggest data experts’ network and exhibiting the most recent trends in the space.  

This is a group for data mining and statistical experts who wish to grow their network of individuals and offer thoughts. Data mining and statistical experts can join this group which makes the number of members to approximately 2 lakh. Methodological issues are reasonable game, as well as discussion of programming (SAS, R, WEKA, and so on), technology (Hadoop, relational databases, and so on) meetings, and job postings etc. are the topics of discussion.  

This LinkedIn group is for analysts, researchers and experts to discuss research methodology, data science, research flow management, research process institutionalization, research automation and growth, just as research competency evaluation and accreditation. This group is uncommonly committed to discussing how functioning with AI can improve research.  

The objective for this expert group is to educate and to talk about various themes and tips from client to-client and to make a worldwide network of individuals already utilizing or keen on utilizing analytics. This group manages Big Data, Data Mining, Statistics, Business Analytics, Predictive Analytics, Prescriptive Analytics, Hadoop, Cloud Analytics, Web Analytics and Text Mining.  

This group is overseen by Bruce Weed, IBM’s Program Director for Enterprise, startups and developers. The group supports discussions on big data and how IBM’s big data platform can deal with client’s big data requirements. Discussions revolve around IBM Platforms and different products and how they can best deal with their database.  

Coordinate Links And Content For Success

For some sites, the process of encouraging links can improve when it’s done together with the content side of a business. I hesitate to call it link building because it’s not really building links in the way it’s commonly thought of.

The reason why content creation and link acquisition should coordinate with each other is because of how tightly Google matches the context between the page where a link is created and the page that the link is pointing to and the search query a searcher is making.

I believe those three matching contexts helps a page rank better.

A link graph is the map of the web, which can be organized by topic and/or niche. The ideal link, in my opinion is from a site that occupies a topically relevant part of the link graph. With enough links, a single page might be able to occupy a topically relevant position in that kind of link graph.

Of course, the page on which the link originates has to be on a topically relevant. And that should ideally exist on a site that is topically relevant. And that site should ideally belong to a topically relevant branch of the link graph.

The importance of the context of a link and and the context of the linked page and how it matches to the intent of a user making the query is important because it may predict a more successful outcome.

For example, during the course of link building I’ve noticed that certain topics are trending and that sites are beginning to link to content that is about that topic.

That’s when I turn to the content side and ask for content about a certain topic. I know that if we produce content on a certain topic we have a higher likelihood of obtaining links for content about that topic.

As someone involved in acquiring links, I am in a position to see that the sites I want links from are talking about a certain topic and that they are linking to other pages that talk about that topic.

Coordinating between the link building side that is looking at sites and the content side that’s creating content can help make a site become more popular.

The link building side may have insight about content topics that the content side might not be aware of.

Seems to me that the typical content and site creation part of a business happens in isolation from the link building part. The link building part is treated as separate. But in my opinion, for some websites, a better outcome will happen if the link building side is an informed partner from the beginning.

On a certain level, link building is understanding what people want and showing them where to get it.

Content is about giving users what they want, what they need and in some cases teaching users how to achieve their aspirations.

Both are focused on users, as is Google when they rank a web page. So if your content and link acquisition is aligned with the users needs, then your page is going to have what users are looking for and Google will find it because of the meaningful and on topic links to those pages.

For that reason, because of how web pages are ranked, link building can’t rightly be considered an activity that happens independently of the content production, PR, site design and social side of a business.

The relationship between the content and social side is a good model of how the content and link building side should cooperate.

And you know, it’s not just links that matter. A quality link building initiative can focus on non-link projects that result in building awareness among important demographic audiences.

A project that puts your message in front of 20,000 potential customers is every bit as good as a link. In the long run, these kinds of projects result in a demand to see your site in the search results. Google search is about showing users pages that meet their needs.

A section of Google’s Search Quality Raters Guidelines is called:

13.0 Rating Using the Needs Met Scale

The “fully meets” rating level, the highest rating, is described as:

“All or almost all mobile users would be immediately and fully satisfied by the result and would not need to view other results to satisfy their need.”

What users need is constantly changing. The link building side can help identify those trends and keep the content side on top of user and website needs.

Coordinating the link building (and awareness building) with the content side may be a useful approach to creating a website that satisfies users and because of that may rank better since it is better positioned to meet user’s needs.

Top 10 Revolutionary Big Data Analytics Companies Of 2023

Here are the top 10 revolutionary big data analytics companies of 2023 that you must take note of it.

Did you know that by 2025, more than 152,000 IoT devices will be connected per minute? The amount of data generated has increased tremendously with the increasing use of AI, ML, and IoT. Big data analytics is helpful in this situation. The technology, also called data analytics, is the foundation of contemporary edge computing. For unfamiliar people, edge computing is a system where processors are placed far closer to the data source or destination than clouds.

These factors will likely cause the big data analytics market to expand rapidly over the coming years. By 2030, this market’s valuation might reach US$745.15 billion. Additionally, a CAGR of 13.5% is predicted for the market between 2023 and 2030. By 2023, the market, valued at US$271.83 billion in 2023, is anticipated to have grown to USD 307.52 billion. Here are the top 10 revolutionary big data analytics companies of 2023.

1. IBM

The New York-based IBM Corporation is a key provider of big data products and one of the top big data analytics firms globally. These include IBM Watson Studio, IBM Db2 Big SQL, IBM Big Replicate for Hadoop, and Cloudera Big Data. These products support ultralow latency data acquisition, processing, and management. Businesses can use these technologies to make decisions more quickly and effectively, lowering their data storage and analysis expenses.

2. SAP SE

The German IT behemoth SAP SE provides businesses with customer-focused goods and services that support data-driven decision-making. Data management tools, including SAP Data and Analytics Solutions, SAP Data Warehouse Cloud, SAP Master Data Governance, SAP Analytics Cloud, and SAP HANA Cloud, are among its products.

3. Microsoft

The Bill Gates-founded hardware and software services company Microsoft Corporation provides customers with tools that make storing and processing various data easy. This covers real-time, unstructured, and structured data. The IT major uses big data and analytics to gather, process, and analyze data.

4. SAS Institute Inc.

The SAS Institute Inc., headquartered in North Caroline, North Carolina, creates a range of technology, including Hadoop, data mining, big data analytics, data management, in-memory analytics, predictive analytics, machine learning, text mining, and cloud computing, to extract the most helpful information.

5. Fair Isaac Corporation

FICO, called Fair Isaac Corporation, is a data analytics business headquartered in San Jose, California. The company supports firms in making smarter decisions to maximize profitability, uncover more significant development potential, and improve customer happiness. Customer growth, decision management and optimization, debt collection and recovery, scoring solutions, and fraud prevention compliance are just a few services the business provides.

6. Oracle

With its global headquarters in Austin, Texas, Oracle Corporation is one of the top suppliers of comprehensive data services that assist businesses in obtaining, handling, sorting, and processing data. The company provides object storage and analysis using Oracle Cloud SQL and Hadoop-based data lakes. It ranks among the top big data analytics businesses worldwide.

7. Salesforce Inc. 8. Equifax Inc.

Equifax Inc., the leading data analytics solutions provider, enables knowledge transformation and enhanced decision-making. These tools assist businesses in making wiser decisions and moving in the direction of improvement.

9. TransUnion

Based in Chicago, TransUnion specializes in big data and analytics technologies that support analytical resources, improve analytical insights, and use analytical tools and specialists.

10. QlikTech International AB

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