Blog

🏆Data Strategy for your Organization – Why’s and How’s

Most organizations these days have jumped on the bandwagon of hiring data scientists, data engineers, data analysts and the never ending jumble of titles referring to data people. Ever since Big Data flooded the scene, organizations have been collecting vast amounts of data from multitudes of sources, not to mention the amounts of unstructured data…
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Data Eats Strategy for Lunch

Someone mentioned last week that there is no such thing as just a Data Strategy and to some extent that is true. Data Strategy,  in my words,  is the blueprint on how a business uses it’s data as an asset in all aspects of its operations to be able to meet its organizational goals and business…
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Step Aside Sales and Marketing

Here comes Data Analytics and Insights! Historically, differentiation as a business strategy has focused on product and market development. Data and analytics have been mere support functions. In the age of digital disruption however, executing a successful data strategy can be a competitive advantage on its own — and that is extremely exciting. With the…
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Governance Impact of Data Veracity on Data Culture

The key issue is that of data accuracy, where the problem is of data veracity. As a general rule, even in the best managed ERP systems, after a short while, we have issues with the veracity of up to 80% of the data, in that we cannot be certain whether the data are accurate or…
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Data Culture

The importance of having a data strategy is two-fold from my experience within several industries. 1. Training Users, Staff and Leadership about data. Lets get them versed! 2 . Streamlining data sources to a data warehouse, lake or one BI Tool environment as much as possible. This keeps integrity of the data as it is…
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Who does the learning when it comes to Deep Learning Models

“The essence of the independent mind lies not in what it thinks, but in how it thinks.” ― Christopher Hitchens, I can’t offer an expert opinion on the limitations of Machine Learning models. I’m new to this field and I hardly know anything about AI and Data Science. The level of my ignorance is only surpassed…
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Why you should not blindly trust your deep learning algorithm?

Why you should not blindly trust your deep learning algorithm? Deep learning is the new poster boy in the world of data science. It has become the heart of of designing intelligent systems. However, all that glitters is not gold! There are surprisingly a few limitations to the deep learning models. Let us explore them…
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🏆Deep Learning:  3 Limits we face trying to replicate the human brain

Deep Learning is a subfield of machine learning comprised of algorithms inspired by the structure and function of the brain. “Deep Learning” is a particularly interesting area of machine learning, because it gets us closer to realizing the true power of AI; however, it has some inherent limitations.  There is a lot of debate around…
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A deep learning model got to know its limitations

Google CEO, Sundar Pitchai said that AI will be more profound than inventions of electricity or fire, emphasizing the impact it will have on the human race. The deep learning algorithms behind the success of AI are the deep neural networks, where the multiple hidden layer learn from exposure to millions of data points. The…
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You, me or it: Nobody is Perfect!

“There is nothing known as “Perfect“. It’s only those imperfections which we choose not to see!!” These words, by the great Albert Einstein aka ‘the Genius‘ himself, sums up today’s article. Deep learning is doing pretty good nowadays & I’m not an antagonist here, but truth to be told, there lies some so called “imperfections”…
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