George Farag on the Hardest Part of AI Careers: What to Learn Next
A computer science student and GDG chapter lead on learning when the tools keep changing - and why mentorship matters more in the AI era.
Articles
Every article on data and AI governance, newest first.
"Move From Fear to Practice": Chad Randall on AI Adoption
Chad Randall, Head of Enterprise at DoxAI, has lived through the PC, the internet, social media and now AI. His advice for adopting AI at work.
Nobody Builds a Career Alone: The Human Side of Red Pico
Why I make time for community stages, students and young professionals - and why leadership practice is rarer than leadership content.
The qualification gets you started
The ability to keep learning keeps you moving. In my conversation with Ashwin Balu, one line stayed with me: "Learn how to learn." His career at IBM has...
Shadow AI was already a problem
Now we're entering the era of shadow agents. An employee creates an AI agent.....Connects it to company data.......Gives it access to an...
Last week, I had conversations with a few leaders - I was there to ask questions
but I walked away with important lessons for professionals at any stage of their career. These individuals (tagged below) reminded me the secret to...
Every AI agent should have a passport
Before an agent enters the enterprise environment, you should know: Who is it? Who owns it? What is it allowed to access? What can it do? What data can it...
Master Data Management may become one of the most important foundations for enterprise AI
Why? Because AI agents need context. An agent working with customers needs to know which customer record is authoritative. An agent working with products...
I think we're entering an era where: Your data strategy IS your AI strategy
Why? Because AI agents don't just need models. They need context. And enterprise context lives in: ->CRM ->ERP ->PIM ->MDM ->Documents ->Knowledge bases...
Imagine opening your enterprise architecture diagram in 2028
and seeing 150,000 AI agents. That's Gartner's prediction for the average Fortune 500 enterprise. For context, Gartner says the number was fewer than 15...
Not every AI agent deserves the same level of governance
That's one of the biggest mistakes I'm seeing in enterprise AI thinking. Consider three agents: Agent A: summarizes documents. Agent B: recommends pricing...
Here's a number that should worry every enterprise AI leader: AI can currently access...
And we're asking AI agents to make decisions. MIT Technology Review Insights found that 55% of executives say their current data systems actively prevent...
A 2-Million-Token Context Window Is Not a Data Architecture
Dumping a database into a prompt doesn't solve search. In the AI era, data engineering is about filtering noise so the model gets the right context.
Every enterprise adopting AI agents needs a new layer in its architecture
I call it the Agent Control Plane. It should answer five questions: Who is the agent? What data can it access? What systems can it change? What decisions...
Why AI Agent Demos Crash Overnight
Agents that shine in a two-minute demo fall apart in a 20-hour workflow. The fix is state persistence, not better system prompts.
Hard Problem: Token Efficiency in Self-Improving Agents Letting an agent reflect on its...
When an agent loops through thinking, critiquing, and fixing its own code, token usage explodes. If you don't control this at the architecture layer,...
Gartner projects that more than 1 in 10 enterprises will be fully “AI-first” by 2030
The defining separator between the winners and everyone else won't be model capability. Gartner's latest Data & Analytics trends report highlights the...
Data consolidation is accelerating at an unprecedented pace
Every enterprise is realizing a simple reality: your AI agent is only as good as the underlying data stack feeding it. The current operational model of...
Stop upgrading your LLM
If your enterprise AI agents are hallucinating, the problem isn't the model—it's your missing data context layer. According to Gartner's CIO & Technology...
88% of enterprises are running AI across core operations
Only 8% have a governance framework to control it. According to Deloitte, while adoption is accelerating, just 21% of organizations have mature oversight...
Last month I was at the Leaders in AI Executive Summit event for roundtable discussions...
It brought together some of the sharpest minds to debate the real-world realities of enterprise AI adoption. Moving to scalable enterprise impact is no...
80% of enterprise AI projects fail—more than double the failure rate of traditional IT...
The root cause isn't the model. It's bad data. Recent 2025–2026 data from RAND, Gartner, and MIT Sloan exposes a critical truth: you cannot build 5-star...
This past weekend, I had the privilege of speaking at the AI, FinTech & Financial Crime...
It was inspiring to share the stage with great leaders and engage with a room full of passionate professionals, students, and technology enthusiasts...
MIT Sloan Management Review notes that 69% experts view agents as a brand-new operational...
Define the explicit boundaries, assign hard human ownership to every domain, and treat digital assets with strict strategic discipline.. 🔗 Read the full...
The truth is painful but simple: the technology doesn't fail; the underlying data...
Bain & Company, in it's four-part series from Roadmap to Reality: Phasing Agentic AI into Production (Eric Sheng, Roger Zhu, Brendan O., Dale P., and...
World's First Formal Government Framework for Agentic AI Governance was launched by...
Their core architectural standard is remarkably simple yet incredibly powerful: you must give every single autonomous agent a definitive, unalterable...
McKinsey partner (Richard Isenberg) recently gathered top CISOs and board directors to...
The panel featured Deneen DeFiore(United Airlines), Guy Gecht (Logitech,SolarEdge Technologies) and Manjula Talreja(Verint, Imprivata, Ping Identity,...
The Harvard Business Review states that modern organizations are facing a critical gap:...
Just as you need a skilled product manager to guide software development, you need dedicated leaders to run autonomous agent fleets at scale. This role...
Anthropic, Open-Weight Models and the Trust Debate
Most of big tech signed a letter against restricting open-weight AI. Anthropic didn't. What each side gets right, and the question it leaves builders.
Deloitte’s latest research highlights agentic AI is scaling significantly faster than...
A shocking market evaluation shows that just 21% of companies possess the capability to govern the autonomous agents they are already running. When you...
The silent rise of 'Shadow AI' inside the modern enterprise
Microsoft’s Cyber Pulse Report exposes that while 80% of Fortune 500 firms run agents, 29% of corporate staff are leveraging completely unapproved...
You cannot build an advanced control plane until you know exactly what assets you are...
EY has mapped out a highly tactical blueprint consisting of 6 Steps to Enhance Agentic AI Governance. The framework dictates a precise operational path,...
A chief data officer sat in a high-stakes strategy meeting, reviewing a magnificent slide...
The metrics looked incredible: reduced cycle times, minimized manual data entry, and seamless multi-system routing. He paused the presentation and asked a...
An enterprise engineering director went to bed confident that his new automated customer...
He woke up to an urgent compliance alert and a flurry of customer complaints. An autonomous data-routing agent had silently bypassed its internal...
How to Put Guardrails on a Black-Box AI Model
You don't need to rewrite a model's weights to govern its behavior. Prompt architecture and output monitoring are the practical perimeter.
Stop Writing SOPs: Capture Them From Real Work Instead
Documentation doesn't need to be a multi-month writing project. Record the work, let an LLM structure it, and review in thirty seconds.
We are currently witnessing a massive, multi-billion-dollar race across the technology...
Every week, a new frontier model is announced boasting higher benchmarks, larger token windows, and faster execution speeds. But for the modern enterprise...
Why do so many well designed enterprise AI initiatives collapse the moment they encounter...
It is rarely due to a system crash. It is because of four silent project killers that slowly degrade accuracy, adoption, and alignment behind the scenes....
A vague requirement: 'The system should ingest customer logs and provide a real-time...
To bridge this execution gap, I advocate IBM'S 5 Layer Context Model. An AI Epic cannot be committed unless it satisfies all 5 Context Layers. Layer 1 is...
How do you take abstract, high-level corporate governance concepts like 'AI Ethics' and...
For most organizations, ethical AI is just an un-executable paragraph written inside a corporate slide deck or a legal policy memo. But if an ethical...
When an enterprise AI transformation collapses, the executive team almost always points...
They blame a hallucination, attack the vendor's software capabilities, or claim the algorithm wasn't advanced enough for their industry. But if you look...
How do you balance data governance with the execution speed of your agile engineering...
Traditional governance functions like a bottleneck—a manual review that stalls deployments right at the finish line. We must stop treating data readiness...
More than 4 out of 5 corporate AI projects stall, break, or get completely canceled...
At PM Ignite 2026, I broke down the root cause behind this staggering 80% baseline pilot failure rate. The failure is almost never a failure of the...
When an AI agent can query sensitive enterprise data via natural language, 'governance'...
I recently finished listening to a fascinating discussion on the AI in Infrastructure podcast with Anahita Tafvizi, Chief Data & AI Officer at Snowflake,...
How do we actually map data domains to functional business domains?
Most enterprise data mapping initiatives completely collapse because they start inside a database instead of inside a business unit. If you are trying to...
In 2026, the role of a founder has transformed from a manual builder to a system...
Anthropic just dropped a comprehensive roadmap detailing exactly how to leverage AI tools like Claude to build a self-sustaining business from day one....
Bypassing security perimeters to hoist a massive flag on top of the Empire State Building...
Deploying live agentic workflows without runtime guardrails is the enterprise equivalent of leaving the roof hatch unlocked and hoping nobody climbs. Data...
Happy Canada Day! Let's build foundations that last. 🇨🇦 The Canadian Pacific Railway...
Let's build foundations that last. 🇨🇦 The Canadian Pacific Railway unified a vast nation because trust was engineered into a shared, physical...
Data management terminology can easily blend together into an intimidating wall of...
The next time someone tries to overcomplicate these layers to sound sophisticated, use this simple blueprint to cut through the noise. 🔹 Metadata: Data...
The path of innovation isn't just about keeping pace—it's about building a relentless...
The recent Databricks Data + AI Summit dropped some massive updates, but two announcements got my attention: Omnigent: An open-source layer to build,...
I was grateful to present 🙏 at the PMI Lakeshore Ontario Chapter Ignite 2026 conference...
I appreciate all the positive feedback 👍 but what struck me most wasn't just the sheer volume of leaders in attendance 🧑🤝🧑, but how deeply engaged and...
Enterprise AI is facing an architecture crisis
Every department is building its own isolated chat or code-generation assistants. This tool sprawl creates an uncontrolled chaos of unmonitored spend,...
Everyone is talking about context when it comes to AI
Have you ever wondered what all these terms mean? Data management terminology can easily blend together. Let's look at what the most commonly talked about...
Beyond AI Innovation Theater: 8 Pillars of a Trusted Data Foundation
Automating business processes puts your operational integrity on the quality of your context. The 8 structural pillars leadership has to mandate.
Audit Debt: The Hidden Cost of AI Automation
AI built a 20-hour DCF model in 30 minutes for under a dollar - with one input error that broke the valuation. Why the new job is auditor, not builder.
Uncertainty stalls enterprise AI
Technology is rarely the issue. When organization leaders find AI adoption moving too slowly, they often look to blame the technology. However, the true...
The boardroom wants agentic AI
The basement has broken plumbing. That gap kills innovation. Executives sit in clean, high-level meetings discussing grand generative visions, intelligent...
Everyone is chasing AI
Few are doing the groundwork. That is a major problem. Enterprises are fighting for space in the "AI Solutions" lane. They are desperately looking for a...
If you are a data governance and soccer fan, then this is for you
I was honoured to be part of this initiative and represent Canada 🇨🇦 to the AI Governance World Cup along with Taylor Owen, @Saswati Soumya Sahu and Mary...
How Do We Explain AI to the Next Generation?
Data leaders spend all day governing models. Teaching kids about AI safely is a different skill - and Tiankai Feng's children's book is a good place to start.
Too many organizations are treating AI governance as an add-on to their existing data...
That is a dangerous mistake. While they are deeply interconnected, their scope and focus are fundamentally different. Data Governance manages the data: It...
The hardest part of an enterprise AI strategy is almost never the AI
It is fixing the legacy data sources you don’t fully trust. Most organizations still treat data governance as an isolated side project rather than the...
Why do so many AI projects look flawless in a Proof of Concept (POC) but fall completely...
When you build a POC, you control the playground. The dataset is perfectly curated, the size is limited, and the system is implicitly fine-tuned to answer...
64% of companies are launching advanced AI projects but
ONLY 7% actually have the data foundation needed to scale them. A brand-new Accenture report reveals this striking gap. Imagine that! Most companies are...
The irony of the 'perfect' framework is that nobody actually uses it
You spend months building a flawless new process. The documentation is pristine. The compliance boxes are all checked. Then you launch it to the team. And...
The greatest operational risk in the era of autonomous enterprise AI is the illusion of...
Many leadership teams assume that deploying a faster, larger model will inherently accelerate business outcomes. But when you strip away the technological...
It is very rarely that you get to spend an entire day talking and listening to leaders,...
What a day at the PM Ignite 2026 Conference! Here is the rapid-fire breakdown from an incredible speaker lineup and thankful to share the stage with these...
The biggest misconception in enterprise tech today is that you can build trust at the...
You cannot patch a lack of data integrity with a highly sophisticated algorithm. Right now, leadership teams are rushing to deploy autonomous business...
In mid-2000s, data debt was an invisible problem
You could sweep duplicate records, poor definitions, and unmapped metadata under the rug for a long time. A human analyst would usually spot the error in...
The best enterprise AI models are completely useless without clear boundaries
In fact, the more powerful your model is, the faster it will make catastrophic mistakes on messy data. Right now, executive teams want to deploy...
Most enterprise AI failures aren’t technology problems
Leaders want to talk about how many autonomous agents they have running. They want to talk about the massive scale of their new language models. They want...
For the last 20+ years, I’ve watched enterprise leaders chase the exact same mirage
In 2005, it was the newest Enterprise Data Warehouse. In 2015, it was the ultimate Data Lake. Today, it’s the latest, greatest LLM or AI agent. The trap...
Five years ago, strong data governance felt like a nice-to-have compliance exercise
Today, it is a business necessity. Not just for risk management. Not just for IT departments. But for any organization that wants to successfully deploy...
Adopting n8n will create disruptive advantage for your Enterprise
While other organizations are stuck paying public cloud platforms, forward-thinking architecture teams are completely rewriting the rules of AI...
SpaceX IPO is on Friday
For data engineers, architects, and governance folks, the most wild part of the pre-IPO prospectus is their plan for Orbital Distributed Compute. They are...
4 Governance Oversights for deploying autonomous systems at scale I attended the Agentic...
As enterprises transition from chatbots to autonomous systems, the conversation is shifting from capability to control. Deploying agents that can actually...
3 Most Critical Insights from Agentic AI Conference 1
Context Engineering > Prompt Engineering: The future belongs to those who can manage the "memory" and "data access" of their agents. 2. Sandboxing is...
Autonomy Without Accountability: When an AI Agent Eats Your Budget
An autonomous agent burned a month of API budget in one afternoon. The lesson: agents need governance policies before they need more autonomy.
Humanizing Data: 5 Lessons on Data Leadership in the AI Era
Why data governance is an accelerator, not a brake - five lessons from a conversation with Tiankai Feng and Prash Chandramohan.
Grateful to share our latest Data Wars Podcast episode alongside Prash Chandramohan — and...
Helena doesn’t just “talk AI.” She connects it to what really matters: people, trust, equity, and impact. From her non-linear journey (film → psychology →...
Grateful for the conversation and insights 🙏 The latest episode of Data Wars Podcast...
Mark brought rare clarity on why causal AI matters now more than ever — from risk-adjusted decision-making to understanding what actually drives business...
DATA LEADERS — THIS EPISODE IS DIFFERENT
I’m still buzzing from our latest Data Wars Podcast conversation with Rudy Ionides — authentic, experienced, battle-tested data leader. In his journey to...
Last week at the GDG Mississauga Tech Mixer, we had the pleasure of hearing Parasar Saha...
Some key insights that really stood out: 💡 Founder-led sales is gold — don’t rush to hire expensive sales teams early. Start with your network, leverage...
Honoured to attend the AI Gathering @ Elevate held by Google (Sabrina Geremia) and hear...
Minister Fedeli’s opening remarks were inspiring — a strong reminder of how far Ontario’s tech ecosystem has come and the momentum we’re building...
Databricks just announced Free Edition, giving everyone access to powerful cutting edge...
Databricks Academy is now offering all self-paced courses for FREE! • Build AI agents and applications using Mosaic AI • Collaborate on data science and...
I’m thrilled to invite you to tune in to our latest episode of Data Wars Podcast where...
If you’re curious about how AI is reshaping industries or looking for actionable strategies to bring AI-driven innovation into your organization, this...
Live Now - Explore Data Products on Data Wars Podcast
Join me and Prash Chandramohan for an electrifying episode featuring the trailblazing Kranthi P Kalagara of Datalinks – a visionary in the realm of data...
Big news - I am launching Data Wars Podcast 🎙️with Prash Chandramohan 🎧 Introduction...
Join us as we dive into the world of #cloud, #data, and #AI. Each episode features conversations with industry experts who share their insights,...
I had the honor to present the keynote on Responsible AI at #Devfest Mississauga last...
As AI reshapes our world, building trust and accountability is essential. My talk highlighted practical approaches to AI Governance—ensuring our AI...
As organizations expand their AI capabilities, scalable AI governance frameworks are...
From automated compliance checks to risk management protocols, governance frameworks help maintain control. AI governance is not a one-size-fits-all...
Transparency in AI algorithms and decision-making processes builds trust and minimizes...
Implementing AI governance practices ensures accountability and fairness. Integrate AI model explainability tools to enhance transparency and...
AI governance is becoming essential as organizations scale their AI initiatives
Ensuring compliance, managing risk, and protecting sensitive data are key components of an effective governance strategy. Establish an AI ethics committee...
AI models are only as good as the data they’re trained on
Ensuring high data quality is crucial for AI to deliver accurate predictions and insights. Develop a data quality framework that aligns with your AI...
Did you know that poor data quality can cost businesses per year?
It impacts decision-making, customer satisfaction, and compliance. Establish a data stewardship program to maintain high data quality standards across...
Accuracy, completeness, consistency—these are just a few of the metrics that define data...
Monitoring these metrics helps identify issues early and maintain data integrity. Set up automated data quality monitoring with alerts for any...
Without high-quality data, even the most advanced analytics tools are ineffective
Investing in data quality ensures that your insights are accurate, reliable, and actionable. Conduct regular data profiling and cleansing activities to...
Metadata isn’t just for organizing data; it’s also critical in training AI models
Properly labeled and categorized data enhances AI accuracy and insights. Ensure your metadata management platform supports AI initiatives by providing...
By offering context, metadata transforms raw data into valuable insights, promoting a...
Organizations with robust metadata management systems see improved data collaboration and reporting accuracy. How are you using metadata to drive a data...
Data lineage isn’t just a buzzword; it’s crucial for regulatory compliance and ensuring...
Metadata management systems track data lineage, making compliance audits seamless. Integrate automated metadata capture to build and maintain accurate...
Metadata provides critical context to your data, making it easier to locate, understand,...
Without proper metadata, finding data assets is like searching for a needle in a haystack. Implementing a metadata management system enhances data...
From manual spreadsheets to automated platforms, the way we manage reference data has...
Today, organizations leverage RDM solutions that integrate with MDM and data governance frameworks. Are you still managing reference data manually? It...
Inconsistent reference data can lead to reporting inaccuracies and compliance risks
A robust reference data management system ensures consistency and alignment with industry standards. Consider implementing automated validation checks to...
Reference data is the backbone of your enterprise systems—think codes, classifications,...
Best practice? Maintain a centralized repository for all reference data and ensure it’s up-to-date to avoid discrepancies. What challenges have you faced...
In an era of digital transformation, MDM ensures businesses have accurate, consistent,...
This enables seamless integration with AI, analytics, and cloud technologies. Prioritize data standardization and choose the right technology platform to...
Many businesses struggle with MDM implementation due to a lack of executive buy-in and...
Without these, your MDM initiative is at risk. To start right, build a clear governance framework and ensure stakeholders align with your MDM vision. Have...
Investing in MDM isn’t just a tech decision; it’s a business value decision
Companies that adopt MDM practices often see improvements in operational efficiency, faster time to market, and increased sales. Gartner estimates these...
Master Data Management (MDM) is essential for consistent and accurate data across your...
It’s not just about managing data; it’s about creating a single source of truth that supports better decision-making. A simple starting point? Identify...
Most of us can write a prompt to get something out of ChatGPT that helps us once, but...
This is a missing skill set - it’s a big hole in most companies right now, and a great way to find your first gig and be recognised for good work.
LinkedIn is training AI Models on your data
For non-EU users you are opted in by default. If you do not want LinkedIn to use your data to train AI then Opt out here in 2 seconds:
Dear companies, it's 2024, and guess what?
Bad data still exists. If you're still wondering whether MDM, EDM, or Data Governance are important, I have a wild suggestion: Why don't you try......
Data Governance isn't just about compliance and control – it's the key to unlocking...
When data is governed properly, it becomes a trusted asset that can drive insights, reduce risks, and support decision-making at every level of the...
It was a great experience to deliver the opening keynote at the Build with AI event this...
It was an honor to share insights on The Path Forward with AI and discuss how we can strategically navigate the rapidly evolving AI landscape. The AI...
Sridhar Ramaswamy is the CEO of Snowflake and he recently talked about leading a high...
Key lessons: 1. Constant Reinvention: What worked yesterday may not work today. To maintain high growth, you must adapt to new realities and avoid...
Tracking data lineage is crucial for understanding the journey of your data from source...
It provides transparency, helps identify potential data quality issues, and ensures compliance. Knowing where your data comes from and how it’s used is...
A unified data glossary ensures that everyone in your organization speaks the same data...
By standardizing terminology, you reduce misunderstandings and improve collaboration. This leads to better data governance and more consistent outcomes....
A unified data catalog is essential for effective data governance
It acts as a single source of truth, enabling easy access and discovery of data. This not only streamlines data management but also empowers business...
Data quality is the key to trustworthy insights
Without strong data quality practices, even advanced data platforms can fail. Ensuring accuracy, consistency, and timeliness across all data zones is...
Policies are the backbone of any data platform architecture
They ensure consistency, compliance, and security across all data processes. From data quality to cataloging and lineage tracking, robust governance...
Data Governance isn’t just about managing data—it’s about protecting it
When governance practices are aligned with privacy objectives, organizations can ensure that data is not only well-managed but also secure from...
The intersection of Data Governance and Data Privacy is where security meets compliance
By implementing governance policies that prioritize privacy, organizations can meet regulatory requirements while safeguarding their data assets. How are...
In today’s regulatory environment, Data Privacy is a top concern
But privacy can’t be achieved without strong Data Governance. Governance frameworks help ensure that data is classified, managed, and protected according...
Robust Data Governance practices are essential for effective Data Privacy
By clearly defining data ownership, access controls, and data handling procedures, organizations can better protect sensitive information. This alignment...
Data Governance and Data Privacy go hand in hand
While data governance ensures that your data is accurate, consistent, and well-managed, data privacy focuses on protecting that data from unauthorized...
One of the most critical data quality metrics is integrity
This metric ensures that data remains accurate and consistent as it moves through different processes and systems. Strong data integrity supports reliable...
Timeliness is a data quality metric that often gets overlooked
Data needs to be up-to-date to be useful. Tracking timeliness ensures that decisions are made based on the most current information, enhancing the value...
In data quality, consistency is key
This metric tracks whether your data is consistent across different systems and departments. Inconsistent data can lead to confusion and errors,...
Completeness is another crucial data quality metric
Incomplete data can lead to flawed analysis and poor decision-making. By regularly monitoring data completeness, organizations can ensure that they have...
Data Quality is more than just a nice-to-have—it's a critical component of data governance
Tracking the right data quality metrics ensures that your data is accurate, complete, and reliable. One key metric to watch is accuracy—how well does your...
Data Governance might sound like a buzzword, but it’s essential for modern organizations
It ensures that your data is managed in a way that’s consistent, secure, and aligned with business objectives. This governance foundation is what drives...
Effective data management starts with robust data governance
It’s the process that aligns your data strategy with your business goals, ensuring that your data is a reliable asset. Think of it as the backbone that...
Why is data governance so important?
Because it provides the framework that keeps your data consistent, trustworthy, and compliant with regulations. Without it, decision-making becomes risky,...
At its core, data governance is about control and accountability
It ensures that the right people have access to the right data at the right time. This structured approach forms the backbone of any successful...
Data Governance is the foundation of effective data management
It’s all about establishing policies, processes, and responsibilities to ensure that data is accurate, accessible, and secure. Without data governance,...
Integrating MDM with your existing systems can be complex, but it's crucial for...
Best practices include incremental integration, continuous monitoring, and using automation where possible. What are your best practices for integrating...
Effective Master Data Management is about more than just technology—it's about governance
Establishing clear ownership and accountability for data ensures that your MDM efforts are sustainable and effective. How do you govern your master data...
One of the key challenges in MDM is maintaining data consistency across multiple systems
Regular audits, data cleansing, and governance frameworks are essential techniques to keep your master data accurate. What strategies do you use to...
Best practices in Master Data Management focus on centralization and standardization
Creating a single source of truth for your data ensures that all teams have access to consistent, accurate information. This reduces errors and enhances...
Master Data Management (MDM) is the cornerstone of a unified data strategy
By centralizing your master data, you ensure that every department is working with the same accurate information. Consistency across systems starts with...
Reference data governance is more than just a checkbox on your data management plan
It's a strategic asset that supports accuracy, consistency, and trust in your data. Don’t let reference data be an afterthought. How is your organization...
Data consistency is key to any successful data governance initiative
And reference data is the foundation of that consistency. By governing reference data effectively, organizations can avoid costly errors and...
Reference data might not be glamorous, but it's essential
It ensures that terms, codes, and classifications are consistent across your entire organization. This consistency is what drives reliable analytics and...
When it comes to data governance, reference data often goes unnoticed
But its role in maintaining data consistency is crucial. Effective reference data management supports data accuracy, making sure everyone in your...
Reference data is the unsung hero of data governance
It acts as the backbone for ensuring consistency and accuracy across all data systems. Without well-governed reference data, even the most sophisticated...
Build an AI First Organization by using this Framework for Adopting LLMs
Embarking on the journey of LLM adoption might seem daunting, but the steps from Scotiabank make it clear and achievable. 1. Start with public chatbots....
Data Dictionary is the same as Data Catalog ?
A Data Dictionary is a list. It’s a collection of terms, definitions, and metadata. Think of it as a glossary of your data. A Data Catalog is a map. It...
Is Data Governance more an art and less science ?
I have never thought about Data Governance being an art but viewing Data Governance as an art form resonates deeply. Just like an artist who adapts their...
Before diving into AI, it's crucial to build a solid data strategy
Too many executives treat AI like magic, overlooking the importance of data quality, completeness, and engineering. A well-defined data strategy is...
Proactive Data Governance is not just a trend—it's a necessity in today's digital...
With the rise of high-profile data breaches, organizations can no longer afford to be reactive. Proactive governance means anticipating risks,...
Unstructured data is everywhere, and governing it is one of the biggest challenges...
Traditional governance frameworks often fall short when dealing with the complexity of unstructured data. But this type of data—like emails, documents,...
The Shift Left approach is revolutionizing data governance
Shift Left represents a proactive approach to data governance that emphasizes integrating governance practices earlier in the data lifecycle. By...
Regulatory compliance is becoming increasingly complex, and data ethics is more important...
As regulations evolve, organizations must stay ahead to ensure they are compliant and ethically sound. Data ethics goes beyond just following the...
Real-Time Data Governance will be a game changer
As businesses operate at lightning speed, the need for real-time data management is critical. Real-time governance means making decisions based on the...
Decentralized Data Governance is no longer just a concept
Organizations are moving away from centralized control, empowering teams to take ownership of their data. This shift is making data more accessible to...
In the age of AI, data quality has become more crucial than ever
AI depends on accurate data to make informed decisions. If the data is flawed, the results will be too. AI is revolutionizing how we manage data quality....
Lately, I’ve had a lot of discussions on different roles in data governance
I want to discuss one of the most important role- Data Stewards. Data Stewards are crucial for managing and optimizing enterprise data. They ensure...
Boost Your Data Quality...Tired of dealing with data quality issues?
Here's how to tackle them effectively: 1. Build a Strong Foundation: Establish a robust data governance program and clear ownership structures to ensure...
The Artificial Intelligence Act (AI Act) is a groundbreaking regulation that sets a...
Here are my key takeaways: 1️⃣ The AI Act establishes a common regulatory and legal framework for AI within the EU, providing consistency and clarity...
Last few months, I have met people fascinated by AI but overwhelmed by the rapid changes
After discussing the trends, here’s what I realized about the future of AI: AI will become a part of our daily routines, from personalized healthcare to...
Client wanted to improve their data quality but resisted implementing a data governance...
They insisted they needed better data quality, not data governance. But can you achieve high data quality without data governance? I don’t think so. Data...
AI alone isn’t a silver bullet, especially if your data is disorganized
Lack of a strong data governance program can turn AI into a liability. It can result in compliance issues, inefficiencies, unethical practices, poor...
Data must be Known, Owned, and Honed
I just listened to podcast discussion between Martin Couturier, Director of AI Innovation at Sage Consulting and Marla A. Dans, data management and...
Garbage In = Garbage Out This is true for all things in life
So why expect AI to be any different? If we feed AI bad data, we get bad results. Data quality is crucial for AI performance. Accurate and diverse data...
AI can make sense of unstructured data and automate processes
AI-first startups in legal, tax, compliance, and financial services are leading the way. AI agents can handle basic tasks and extend human capabilities....
Progress Over Perfection Each error teaches us something valuable, pushing us to improve...
In the realm of data governance, project management, or any field, striving for perfection can lead to paralysis. Small, consistent steps lead to...
How do you ensure effective documentation of your data pipelines within your Data...
Documenting data pipelines is a cornerstone of robust Data Governance. It ensures transparency, traceability, and efficient troubleshooting, which are...
AI Governance Comprehensive: Tools, Vendors, Controls & Regulations.' is coming out in...
This extensive guide covers 90 vendors and 90 controls, with mappings to the EU AI Act. At 362 pages, it's packed with valuable insights and will be...
4 Practical steps to Maximizing Business Impact Through Data Governance
Just attended a session "Maximizing Business Impact Through Data Governance," presented by Dan Mazur where he delved into key strategies for leveraging...
In an era where AI is the ship navigating the vast digital ocean, Data Governance is the...
It's not just about managing data; it's about unleashing its potential responsibly and strategically. Let's discuss how Data Governance is shaping the...
AI at the Forefront
This year, I'm diving deep into the world of AI, and it's been an enlightening journey so far! 🧠💡It is clear that for organizations to have success with...
Data Governance 101: Data governance is the process of managing, organizing, and...
How can you implement data governance in your organization? ✅ Appoint a data governance team with clear roles and responsibilities. ✅ Create a data...
The only person who never makes a mistake is someone who does nothing
Albert Einstein As a data governance professional, I have learned that making mistakes is a natural part of the learning process. It's easy to get...
This diagram reminds me of work i do everyday to help enterprises govern their data
As organizations continue to generate and collect massive amounts of data, effective data governance involves managing the entire lifecycle of data, from...
As data becomes an increasingly valuable asset for businesses, it's important for...
There are several key components to a strong data governance program: 1. Data ownership: It's important to clearly define who owns the data within an...
Wow ! Team Collibra knows how to put an event together, the Data Citizen Conference was...
Team Collibra knows how to put an event together, the Data Citizen Conference was packed with Data Leaders from across the industry. Congratulations to...
How is your data doing?
Before the start of any journey you need to have a plan. Likewise all digital transformation journey's need to begin with understanding the current state...
Attended some sessions in TransformX - AI & ML Conference today
I really enjoyed Fireside Chat with Greg Brockman, President, Chairman, and Founder, Open AI & Alexandr Wang, CEO & Founder, Scale AI and The State of AI...
Watch the full keynote from Satya Nadella - so many exciting things to transform the tech...
1. Love the new Designer - Text to Image AI - designer.microsoft.com 2. AI Code Assistant - Game changer - Github Co-Pilot 3. Microsoft Syntex - game...
Unlock more value from your data by treating it like a data product
For Example provide datasets with a 360-degree view of an important entity, such as customers, employees, product line etc. Oprationalize governance of...
Get your data organized if you want to be successful with AI
Julien Ballot , CEO, Scale AI Invest significantly in #datagovernance and #datamanagement practices and be ready for the long journey. Collaborate and...
Excited to attend the Big Data and AI Toronto
Sharieff Mansour talking about Culture and Core AI principles which organizations need to follow to be successful with AI. Starbucks success story with ML...