Laying the Foundation for Your Digital Transformation

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Digital transformation is a concept that has become so mainstream it has morphed into a catch-all buzz phrase that, at best, is confusing. At its worst, it’s meaningless. Truth is, the idea is going to mean different things for different organizations. Think of digital transformation as being “in the eye of the beholder.”

Let’s agree on this much: It ultimately marks a radical rethinking of how an organization uses technology, processes, and people to evolve its business performance and eventually drive profitable growth and customer success. 

But again, digital transformation can be a proxy for a wide range of innovations and strategies as organizations try to stay on the cutting edge. In fact, it can be as much about how individuals work and the cultures of organizations as it is about technology.

So, how ready is your company as you embark upon this complex undertaking? 

There are some key areas that organizations must get right to ensure a successful digital transformation:



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EdTech Evolution: Recap Of Top 2019 Trends And Those Expected To Rule 2020

This article on EdTech Evolution first appeared in BusinessWorld here.

There is no doubt that education is the key to transform lives. But now that we are living in the age of digital technologies, we are quickly getting accustomed to seeing education itself being transformed by leaps and bounds. The coming up of new-age players in the online education space has innovated both the nature and quality of education, and it is just the beginning of EdTech evolution.

EdTech Evolution: Recap Of Top 2019 Trends And Those Expected To Rule 2020


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Top 7 sectors expected to drive digital transformation in India

It is no secret that digital transformation has been driving industry-wide disruptions for the past two decades, enabling businesses across sectors to achieve massive scale and growth. However, much of the economic potential still remains untouched by industries. As per MGI predictions, digitization holds the key to unlocking this potential, which will enable the global GDP to gain USD 13 trillion by 2030

In fact, various industry leaders believe that technology education — forms the foundation of digital transformation — can help double the world’s GDP. Riding on the back of AI, Machine Learning, Cloud Computing, Data Science, SaaS, IoT – the next wave of transformation is certainly going to require ample upskilling and reskilling.

Top 7 sectors expected to drive digital transformation in India

It is said that a rising tide raises all boats. To begin with, the transformation journey would be led by some sectors and the effects would then trickle down to other wheels of the economy. Here are some sectors which leading digital transformation:



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Navigating an Enterprise Level Digital Transformation

Digital transformation isn’t a clean and simple process. There is no one singular path when it comes to implementing digital transformation within a company. No one knows this better than Chris Hsu, who was the EVP and GM of HPE software business. He was also the Chief Operating Officer of Hewlett Packard Enterprise. After HPE sold the software business to Micro Focus, he became the Chief Operating Officer of Micro Focus. Chris joined our COO, Lalit Singh to discuss how companies can lead effective digital transformations in our latest Thought Leader Webinar Series.

Digital transformation marks a radical rethinking of how an organization needs to use  technology, people and processes to fundamentally change business performance, Chris Hsu stresses. “Frankly, in today’s day and age, I think that if you are living in old systems and processes, you will be disrupted.”

Fearful of being outflanked by more nimble competitors, companies are seeking to accelerate innovation, experimenting with new digital services and capabilities to augment existing offerings or to slide into adjacent markets. One of the first things companies should do in embarking on a digital transformation is answer this critical question: What business outcomes do you want to achieve?

“It starts with the business outcomes and the new business models you’re going after and working backwards from there,” says Chris Hsu. “There are a number of perspectives to consider including technology, data, and more than anything the people and operational side of the business.”

Companies can follow some key digital transformational tips to affect the kind of change they desire, including:

  • Focus on a clear set of objectives. Whether you’re transforming an existing model or starting from scratch, leaders must reach a consensus on the best path to pursue.
  • Adopt agile execution. Encourage risk taking, enabling even lower-level employees to make decisions, fail fast and learn.
  • Instill focus. Business leaders must recognize it  is a marathon, not a sprint. And in order to present and to be effective over a long period of time, leaders must be mentally and physically fit so they can focus.

While emerging tech and revamped processes are crucial, having the right skills on staff is essential to any digital transformation.

Software engineers, cloud computing specialists and product managers remain key roles for companies seeking to roll out new products and services. DevOps leaders galvanize software development by merging development with operations, enabling companies to continuously iterate software to speed delivery.

Data scientists and data architects are also in high demand, as companies seek to glean insights out of vast troves of data, and transformations lean increasingly on machine learning and artificial intelligence.

Companies can lag in digital transformations for several reasons, a few being poor leadership, disconnects between IT and the business, lagging employee engagement and substandard operations. But, according to Chris Hsu, “I think digital transformation, if you’re doing it correctly, should impact all parts of the organization. Digital transformation has the ability to flatten an organization, and to really start to streamline and remove those manual administrative processes that no one really loves doing, and creates the capacity for more customer-facing interactions,  for more innovation, and fundamentally more building of things.”

This is one webinar, you don’t want to miss. View it here.

How companies need to think about the cloud and digital transformation

Enterprises are at a critical juncture: adopt and adapt technology to meet the 24×7 demands of customers, employees, and partners—or risk becoming obsolete. One of the primary shifts in responding to such demands is cloud computing.

As part of our Udacity Thought Leader webinar series, our very own Lalit Singh, COO at Udacity, sat down with Rahul Tripathi, the CTO and VP of Customer Success at Nutanix to discuss the challenges facing companies looking to embrace the cloud while remaining relevant in today’s competitive market. The conversation anchored on how the cloud is the foundational enabler of digital transformation and offers the scale and speed needed for businesses to grow.

When it comes to transforming the infrastructure of a business, both modernization and automation play crucial roles. For organizations looking to bridge the digital skills gap and attract talent, it’s important to move from outdated to next-generation systems that facilitate innovation. Hear Rahul stress how technical skills and soft skills are critical for any business looking to stay competitive and transform into digital enterprises.

Watch as they discuss:

  • What a modern enterprise cloud strategy looks like
  • Why digital transformation requires the right blend of business, IT and soft skills
  • How organizations can take steps to bridge their hiring and training strategies

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SXSW: How Top Companies Create Training Data

Udacity had the unique opportunity to have two of our thought leaders on a panel discussion on training data for machine learning entitled AI-AI-Oh! during SXSW 2019. The discussion triggered an exchange of viewpoints among the expert panelists which ranged from how the data is being used in various industries, how much training data you need to apply machine learning, and practical tips for the audience to consider.

You can listen to the entirety of our panel discussion here.

The discussion started with the framing of machine learning. Machine learning (ML) is about teaching computers how to learn from data to make decisions or predictions. For true machine learning, the computer must be able to learn to identify patterns without being explicitly programmed to.

An easy example of a machine learning algorithm is an on-demand music streaming service. For the service to make a decision about which new songs or artists to recommend to a listener, machine learning algorithms associate the listener’s preferences with other listeners who have similar musical taste.

Machine learning fuels all sorts of automated tasks and spans across multiple industries, from data security firms hunting down malware to finance professionals looking out for favorable trades. They’re designed to work like virtual personal assistants, and they work quite well.

Machine learning serves a mechanical function the same way a flashlight, a car, or a television does. When something is capable of “machine learning”, it means it’s performing a function with the data given to it, and gets progressively better at that function. It’s like if you had a flashlight that turned on whenever you said “it’s dark”, so it would recognize different phrases containing the word “dark”.

In machine learning projects, we need a training data set. It is the actual data set used to train the model for performing various actions.

ML relies heavily on data; without data, it is impossible for an “AI” to learn. It is the most crucial aspect that makes algorithm training possible. The panelists discuss three different types of training data including:

Client services data – data generated from customers. “At HubSpot, we gather user-generated training data for ML that informs everything from email send time optimization to audience targeting,” stated Hector Urdiales.

User generated data – data created by users on their own without being prompted.  “We train data based on patterns,” said Rob McGrorty.

Simulated data – sensor data that self-driving cars, for example, collect in the real world. “A test vehicle’s cameras might record video of pedestrians crossing the street at night. Software developers can use that video every time they update their self-driving software, to verify that the software still detects the pedestrians correctly,” explains David Silver.

Essentially, training data is the textbook that will teach your AI to do its assigned task, and will be used over and over again to fine-tune its predictions and improve its success rate. Your AI will use training data in several different ways, all with the aim of improving the accuracy of its predictions.

Quite simply, without training data there is no AI. The cleanliness, relevance and quality of your data has a direct impact on whether your AI will achieve its goals.

Be sure to listen to this informative panel discussion and learn more about training data and practical use cases.

Educating Our Way Out of the Data Scientist Shortage

It’s no secret that employers are looking for data scientists. They have become the stars of the modern workforce – the most valuable employees.

Companies of all sizes have awoke to the fact that data science, by mining new insights from even decades of accumulated data sets, has the potential to drive efficiencies and increase productivity in ways never previously imagined. Simply put, it has the potential to transform businesses. From Zillow’s home price predictions to Amazon’s recommendation engines, applications of data science have become increasingly accurate, prevalent, and impactful on our everyday lives.

But while “data scientist” has been ranked the “No. 1 Job in America” for three years running now, according to careers website Glassdoor, there’s still a shortage of talent to fill the huge need of employers across every industry. In fact, according to a recent LinkedIn study, businesses across the nation need 151,717 more data scientists right now.

The need is nothing short of stunning.

This is why companies understand that they must increasingly invest in the education of their employees in order to compete in an ever-changing world. At the same time, employees need to recognize that traditional higher education just isn’t designed or equipped  to keep up with the breathtaking pace of technological developments and digital transformation that we see in business every single day. People may intuitively know that learning is a lifelong process. But the modern employees also needs to accept that that continually adding to their skill set is the best way they stay competitive in the job market.

Here’s the reality: Jobs are available. But organizations expect potential employees (and current ones) to have the skills to those critical jobs.

The advantage of this digital transformation is that it’s also changing how we think about education. And it truly can be the answer to solving the data scientist shortage within your company.

This ongoing process of learning can take place digitally and independently of location. E-learning can happen anywhere, anytime: at the workplace, at home, on the train, or in the coffee shop. The subject matter can even be adapted to the precise, tailored requirements of a company. This way, it has maximum added value for employees and employers. For example, last year the automobile company Audi launched its employee “data-camp” training focused on big data and artificial intelligence.

Even companies that specialize in data analysis have recognized their own crying need to create alternatives to the traditional training pathways. After all, they are on the front lines of the digital transformation, and their workers need to have cutting-edge skills.

For example, our customer Alteryx, which develops self-service data analysis software, offers a nanodegree that enables regular employees to become data specialists and to expand their own career opportunities. In this way, companies meet the need for data specialists, while employees sharpen their skill sets, receive additional qualifications and ultimately improve their career opportunities.

It becomes a win-win. Organizations benefit the improved effort of employees. The workers themselves expand their horizons.

Employees who have a background in computer science or mathematics – and interact with numbers, data and programming daily – are ideal candidates in terms of becoming data experts in the company. Udacity’s online course, with concrete sample projects and application examples, is usually enough to give employees the added education they need to take that next step within their own company.

But employees outside of traditional IT departments have opportunities to pursue what is known in the industry as  “Citizen Data Scientists.”The term describes employees who evaluate data but do not program the algorithms themselves. Instead, they use self-service tools. These tools enable the analysis and visualization of large amounts of data with preconfigured workflows. The advantage here is that employees usually know more about the context of the data and can bring that understanding directly into their own departments.

Data isn’t the future. It’s now. And it’s critical to every company in every industry.

Companies are looking everywhere for data scientists. They can be academically trained, educating through  internal further education programs, or this relatively new world of Citizen Data Scientists, It’s clear that businesses need all of them because we live in  a world where data is collected everywhere. It’s clear that companies need to invest in employee training to keep pace with digital transformation.

Faced with this dire shortage of talent, business leaders who want to make the most of data science can’t rely on half-measures and casual hiring processes. What they need is a strategic roadmap toward building data science skills internally and effectively upskilling their talented employees.

Stay tuned for new releases from Udacity Enterprise.