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Why did I leave IT services? and why I do not regret it.

A lot of people talk about business people being data-driven and AI literate. However, I believe the more important issue is that data professionals need to become business-savvy.

How Do You Know If You Need a Data Strategy? Ask These 5 Questions.

These five questions are not merely a self-assessment tool; they are a strategic compass, guiding executives towards the successful integration of data into the very fabric of their business.

Why Do Kids Lie? What to do as a Parent

Make sure your child feels comfortable talking to you about their thoughts and feelings, and be supportive and non-judgmental in your responses.

Future of Prompt Engineering: Prompt LLMs

This is the"meta-learning" with few-shot. LLM can "learn" on whatever you manage to cram into the context window with "prompt LLMs"

Potential Impact of GPT in the workforce - Scary Stats and Findings

Artificial Intelligence (AI) generally and Generative AI technologies like GPT-4 , specifically, are expected to have a significant impact on the future workforce, with some occupations being more exposed to AI than others.

Deep technical expertise Isn't enough for higher impact: Become a high-leveraged engineer

I have learned that To truly excel, you need three key attributes: great communication skills, business sense, and domain understanding. This worked for me and may work for you as well.

Dear Data Leaders, someone else’s cool AI project doesn't make your project less valuable.

Someone else’s cool AI project doesn’t make your project any less valuable. Don’t let the constant stream of exciting projects and advancements make you doubt your own vision. Keep moving forward and trust in your own unique approach.

Why is a data project delivering valuable insights for users still get failed?

Most of the newly generated insights are not integrated with the business process but are made available as a BI dashboard. Use these SaaS tools to quickly operationalize AI models and any other insight for maximum impact and ROI, check the adoption, and iterate quickly.

How to measure and communicate the ROI of data initiatives in your company?

I have seen many successful data leaders develop a value dashboard that compile and the track all ROI information and KPIs that are being impact by data projects. The main idea is to basically try to translate the data work they do into dollars and time saved.

Rise of Stable Diffusion and transformation of Art with AI

Shopify's AR/VR Product Lead Russ Maschmeyer has demonstrated an interesting and cool prototype service that would allow its users to come up with ideas for real-life wallpapers, preview AI-generated results in AR, and instantly purchase the final product with the exact design a person would want.

Tips for Managing Up: Single most important skill to propel your career

If you are at the top of his attention, over-communicate. If you’re not doing the most pressing thing right now, you have to learn to drop back and do great work. That way, when you do become the top of the attention, it’s for the right reasons, and not because everything is on fire.

Outshine in engineering interviews with the STAR framework

Do you struggle to explain your projects in interviews? Are you unsure how to share your achievements during an interview with the full context? STAR framework will help you prepare for that.

what are productized services? List of Productized data and AI services

Productizing IT consulting services can be an incredibly profitable move. It can help services firms to scale their consulting business and make steps from sales to delivery repeatable and reusable

IT service providers can charge better rates by providing customer-centric services

Customer-centric Professional services providers improve the client’s condition by providing skills, behaviors, content, advice, experiences, and other factors unique to that niche over a designated time.

What is Metric Layer? Why is it increasingly becoming a part of the modern data stack?

A system providing a standard and consistent set of definitions of metrics on top of the data warehouse.

14 Rules of persuasive storytelling for pre-sales consultants

Know your audience, Adapt your vocabulary to match your audience, Make client care, Structure your story - Minto’s Pyramid Principle, Demonstrate competence & Establish your credibility Be Specific with a flexible framework in place, Appeal to the head, heart, and hand

A framework to find your true calling that gets founded the Amazon

How to understand what you should do in life? Every minute spent doing something other than what you love the most today is a minute you will likely regret when you’re old.

How to get promoted fast in an engineering career?

Do you want to excel in the engineering career? Surprisingly, this has very little to do with technical skills. To be a high-leveraged engineer, learn meta-skills like better communication, relationship management, and business understanding once you perfect the basics of your technical skills.

How to send complex technical proposal to a prospect within 5 hours under extreme uncertainty

I will give you a framework on how to engage clients with minimal effort, it's quite normal that you have to send the 1st proposal to a client with very limited information. The proposal needs to be directionally right and open-ended enough to incorporate new details at a later stage.

A profit growth framework for IT services firms

IT services growth does not only mean getting more business. There are other profitability levers that should also be considered like not just to grow in volumes but also think about the rate of profitability per resource.

AI Mindset for a successful enterprise data transformation

The adaptation of the AI mindset and an iterative AI journey will ensure that AI investments are properly executed and more resources are put into the bets that are proven to work in the MVP phase.

The hunter(data scientist) will become the hunted (automated) sooner than we thought

Data scientists are getting automated faster than the rest of the engineers

How AI solution’s maintenance is different from traditional software

IDC predicts that up to 88 percent of all AI and ML projects will fail during the test phase[1]. A major reason is that AI solutions are difficult to maintain. In this post, I will highlight how the maintenance of AI solutions is different and why MLOps is important.

Its critical to do business and technical assessment of the AI solution before(not after) starting the implementation

Imagine that you are either * The Data Scientist, who is going to implement the solution, will require technical feasibility and complexity assessment like is the right data available? how inference will be integrated with the business process? and is the acceptance criteria achievable with the given data set and constraints?

2 Proven ways to launch successful AI Startups

For business-facing (B2B) AI products, it’s often difficult to get the data necessary to build a prototype because a lot of highly specialized data is locked up within the companies that produce it. There are a couple of general ways in which AI teams can get around this problem:

How to do data and ROI feasibility of a machine learning based forecasting solution

A list of key questions that will help asses business and technical feasibility of a machine learning solution Lets take an example of a machine learning and deep learning based forecasting solution. Imagine that you are the Machine learning engineer and want to asses a forecasting use case from two