Sunday, 25 September 2016

Why Data Scientist is top job in Digital Transformation

Digital Transformation has become a burning question for all the businesses and the foundation to ride on the wave is being data driven.

DJ Patil & Thomas Davenport mentioned in 2012 HBR article, that Data Scientist is the sexiest job of the century, and how true!  Even the latest Glassdoor ranked Data Scientist at 1st in top 25 best jobs in America.

Over the last decade there’s been a massive explosion in both the data generated and retained by companies. Uber, Airbnb, Netflix, Wallmart, Amazon, LinkedIn, Twitter all process tons of data every minute and use that for revenue growth, cost reductions and increase in customer satisfaction.

Most industries such as Retail, Banking, Travel, Financial Sector, Healthcare, and Manufacturing want to be able to make better decisions. With speed of change and profitability pressures on the businesses, the ability to take decisions had gone down to real time. Data has become an asset for every company, hence they need someone who can comb through these data sets and apply their logic and use tools to find some patterns and provide insights for future.

Think about Facebook, Twitter and other social media platforms, smartphone apps, in-store purchase behavior data, online website analytics, and now all connected devices with internet of things are generating tsunami of new data streams.

All this data is useless if not analyzed for actions or new insights.

The importance of Data Scientists has rose to top due to two key issues:
  • Increased need & desire among businesses to gain greater value from their data
  • Over 80% of data/information that businesses generate and collect is unstructured or semi-structured data that need special treatment 

Data Scientists:
  • Typically requires mix of skills - mathematics, statistics, computer science, machine learning and most importantly business knowledge
  • They need to employ the R or Python programming language to clean and remove irrelevant data
  • Create algorithms to solve the business problems
  • Finally effectively communicate the findings to management

Any company, in any industry, that crunches large volumes of numbers, possesses lots of operational and customer data, or can benefit from social media streams, credit data, consumer research or third-party data sets can benefit from having a data scientist or a data science team.

Top data scientists in the world today are:
  • Kirk D Borne of BoozAllen
  • D J Patil Chief Data Scientist at White House
  • Gregory Piatetsky of kdnuggets
  • Vincent Granville of Analyticsbridge
  • Jonathan Goldman of LinkedIn
  • Ronald Van Loon

Data science will involve all the aspects of statistics, machine leaning, and artificial intelligence, deep learning & cognitive computing with addition of storage from big data.

Sunday, 18 September 2016

What is Cognitive Computing?

Although computers are better for data processing and making calculations, they were not able to accomplish some of the most basic human tasks, like recognizing Apple or Orange from basket of fruits, till now.

Computers can capture, move, and store the data, but they cannot understand what the data mean. Thanks to Cognitive Computing, machines are bringing human-like intelligence to a number of business applications.

Cognitive Computing is a term that IBM had coined for machines that can interact and think like humans.

In today's Digital Transformation age, various technological advancements have given machines a greater ability to understand information, to learn, to reason, and act upon it. 

Today, IBM Watson and Google DeepMind are leading the cognitive computing space.

Cognitive Computing systems may include the following components:
·      Natural Language Processing - understand meaning and context in a language, allowing deeper, more intuitive level of discovery and even interaction with information.
·      Machine Learning with Neural Networks - algorithms that help train the system to recognize images and understand speech
·        Algorithms that learn and adapt with Artificial Intelligence
·        Deep Learning – to recognize patterns
·        Image recognition – like humans but more faster
·        Reasoning and decision automation – based on limitless data
·        Emotional Intelligence

Cognitive computing can help banking and insurance companies to identify risks and frauds. It analyses information to predict weather patterns. In healthcare it is helping doctors to treat patients based on historical data.

Some of the recent examples of Cognitive Computing:
·  ANZ bank of Australia used Watson-based financial services apps to offer investment advice, by reading through thousands of investments options and suggesting best-fit based on customer specific profiles, further taking into consideration their age, life stage, financial position, and risk tolerance.
·   Geico is using Watson based cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite
·    Brazilian bank Banco Bradesco is using Cognitive assistants at work helping build more intimate, personalized relationships
·       Out of the personal digital assistants we have Siri, Google Now & Cortana – I feel Google now is much easy and quickly adapt to your spoken language. There is a voice command for just about everything you need to do — texting, emailing, searching for directions, weather, and news. Speak it; don’t text it!

As Big Data gives the ability to store huge amounts of data, Analytics gives ability to predict what is going to happen, Cognitive gives the ability to learn from further interactions and suggest best actions.

Saturday, 10 September 2016

Digital Transformation - Top 5 challenges to overcome

The Digital Tsunami is moving at a rapid pace, encompassing all aspects of business and society. It touches every function of a business from purchasing, finance, human resources, operations, IT and technology, sales and marketing and every other division in the business.

Understanding this dynamic and making the necessary changes, is the context for digital transformation. The starting point is to assess your businesses’ state of digital preparedness based not just on technology, but on a comprehensive picture of digital integration and engagement throughout the organization.

Digital transformation poses these top five challenges to businesses of all sizes:

1.   Culture: There is a fear to change with an attitude of why fix something that isn’t broke? Company culture is the basis of digital transformation. Without openness to change, either naturally or as a specific initiative, digital transformation does not go as planned. It is important to remind teams of the benefits that will directly impact them in a positive way. Open communication is important when clarifying the purpose of a digital transformation and identifying the role it will play in their daily work routine.

2.    Lack of Leadership support: Most of the companies C-Suite is over 50 now and are digital immigrants. They have slowly adapted to web surfing, emailing, texting and the instant world of social media. Hence it is difficult for them to drive the digital transformation. They need to set the tone by collaborating with managers on designing an organization-wide digital strategy, while encouraging ongoing innovation. A dedicated Chief Digital Officer is one way to go.

3.    Inter Department collaboration: It is essential that all departments work together to bridge gaps, break down data silos, and make important connections. Companies are challenged to get the right people in their organization to work together to create a consistent experience across the board.

4.  Resource Crunch:  With so many technologies paving up every day, it is almost impossible to have people who know them well. Organizations need to recruit for the future with jobs skills that they have not considered to meet forthcoming changes in the digital marketplace.

5.   Understanding Customer: Companies like Amazon, Uber, Airbnb and Tesla have changed the expectations of the market forever. The average consumer now expects brands to be able to understand their unique wants and needs and create a tailored experience to suit. Most business leaders understand this principle but often find themselves caught in a discussion about technology.

Though these are often the most prevalent challenges cited by organizations going through digital transformation, countless others exist like, identifying right digital opportunities, right technology selection etc.

To meet the manifold challenges posed by digital transformation, individuals and organizations should have the confidence and commitment to make digital integration a strategic imperative. 

The success will depend on whether every employee and manager is ready to anticipate, innovate and participate in each step of Digital Transformation.


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