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  • Don’t Say Startups Are Hard

    Don’t Say Startups Are Hard

    I’ve come to believe that founding something can be one of the best things you can do for yourself during your working life.

    Not because you’ll necessarily build a billion-dollar company. Not because you’ll raise venture capital, have a big exit, or even succeed in the conventional sense. But because the experience of taking an idea and trying to turn it into something real changes you. It forces you to learn, adapt, take ownership, and discover capabilities you might never have needed to develop otherwise.

    And yet, I meet a lot of smart, capable people with genuinely good ideas who never try.

    One reason, I think, is that we founders have become very good at telling everyone how hard it is.

    When I was founding—or had just started—DataIAm, I made a point of meeting other founders. I met many, and I learned a tremendous amount from them. They were generous with their time and advice, and I’m grateful for it. But many also wanted to prepare me for just how hard the journey was going to be.

    Some told me they had reached points where they literally cried. Others talked about moments when they regretted becoming founders, or how much they had sacrificed—the time, the stress, the financial uncertainty, the impact on the rest of their lives.

    These weren’t people trying to discourage me. Quite the opposite. They were sharing hard-earned lessons and preparing me for what might come.

    But as I went further into my own journey, I kept waiting to feel some version of what they had described.

    I didn’t.

    That doesn’t mean building DataIAm has been easy. Far from it. There have been setbacks, uncertainty, long hours, things that didn’t work, things that took much longer than expected, and plenty of moments when I’ve had to rethink the plan.

    But regret? No.

    And I’ve been thinking about why.

    The closest analogy I can find is something else I spend time doing: working out.

    Nobody goes to the gym because it’s easy

    A good workout is hard. You make time for it when you’d rather be doing something else. You control your diet. You push your body beyond what’s comfortable. Sometimes you add weight when the current weight is already difficult. Sometimes an exercise that worked well for months stops producing results, so you have to find another way to challenge yourself.

    You experiment. Change the weight. Change the repetitions. Change the exercise. Learn a new technique. You adapt.

    Building a startup feels remarkably similar.

    Something that worked with beta customers may not work with others. The product you were convinced people needed may not be quite what the market wants. You run short on resources. A competitor changes the landscape. A new technology suddenly makes possible something that wasn’t possible six months ago.

    So you adjust. You learn, build, throw things away, rebuild, and find another way.

    Of course that’s hard.

    But here’s the thing about a workout: the effort starts paying you back almost immediately.

    The return doesn’t begin when you reach the goal

    When I go for a run, I don’t have to wait until I’m faster to get something from it. When I go to the gym, I don’t have to wait until I’ve gained muscle to decide whether today’s workout was worthwhile.

    The visible results come much later, but the mental reward is immediate: the satisfaction of pushing yourself, the feeling when you finish something difficult, the small realization that you did something today that you couldn’t—or wouldn’t—have done before.

    Nobody else may see any of it. But you experience it. The payback is already there.

    And I think that’s why I’ve never related to the idea of regretting the effort of building a startup.

    The startup is paying me back while I’m building it.

    Most startup returns are invisible

    From the outside, we tend to measure startup success through visible outcomes: revenue, funding, headcount, valuation, acquisition, IPO. Those are the long-term, visible gains.

    But founders experience hundreds of smaller, mostly invisible returns along the way: the first time someone you don’t know uses something you created; the first customer who gives an unsolicited shoutout; the first time an idea that existed only in your head becomes a real product on a screen.

    It’s the problem everyone thought would be difficult that your team finally solves. The moment you realize your original idea was wrong—and that you’ve figured out a better one. Watching someone on your team grow beyond what either of you expected. Learning a technology, an industry, a sales motion, or a part of business you knew almost nothing about a year earlier.

    And sometimes it’s simply figuring out how to get around the latest obstacle.

    Most of these moments won’t make a headline. They probably won’t make your LinkedIn feed either. But you know.

    That’s the part of entrepreneurship I don’t think we talk about enough.

    An exit isn’t the only reward

    We have a tendency to tell startup stories backward. Once a company becomes worth billions or gets acquired, we look back at all the struggles and sacrifices and say, It was worth it.

    But what if there isn’t a billion-dollar outcome? What if there isn’t even an exit? Was all that effort somehow wasted?

    I don’t think so.

    That would be like saying years spent exercising were worthwhile only if you eventually won a bodybuilding competition. The workout was doing something for you every single day.

    So is building something.

    You learn how to operate with incomplete information. You learn to sell, build, and persuade people to believe in something that doesn’t fully exist yet. You learn to make decisions when nobody can tell you the right answer, and to recover when something you were certain about turns out to be wrong.

    Perhaps most importantly, you discover what you’re capable of when there isn’t a large organization around you providing the structure.

    Those are returns too.

    Build something once

    This is why I’ve come to believe that, for many people, founding something at least once can be one of the most valuable experiences of a career.

    It doesn’t have to be the classic Silicon Valley venture-backed startup. Build a lifestyle business. Start a consulting practice. Create a nonprofit or a philanthropic project. Build a small product around something you understand unusually well.

    Take an idea you care about and try to turn it into something real that didn’t exist before. Find your version of it.

    Will it require sacrifice? Almost certainly. Will there be moments when you have to push beyond what feels comfortable, change direction, learn something new, or find another way when the obvious approach stops working? Absolutely.

    That’s also what happens when you train seriously.

    But we don’t tell people not to exercise because exercise is hard. We tell them what it can do for them.

    Maybe we should talk about entrepreneurship the same way.

    When founders tell you how hard it is, listen to them. They’re probably telling the truth. I certainly don’t want to minimize what any founder has experienced—or the very real sacrifices some have had to make.

    But don’t stop listening at the word hard. And if you have an idea you genuinely believe is worth trying, don’t let someone else’s horror story become the reason you never find out what you could have built.

    Because the reward doesn’t begin when you raise money, reach profitability, or get an exit.

    Just like a good run or a hard workout, the effort can be part of the reward.

    The payback can start today.

    And once you see it that way, the question becomes:

    What’s to regret?

    ————————————–

    To learn about my startup, visit: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • Why We Built DataIAm for FSC

    Why We Built DataIAm for FSC

    Enterprise integration wasn’t supposed to be the hard part. At least that’s what I thought when I joined Salesforce Industries in 2016.

    Before Salesforce, I worked on enterprise integration products at IBM Cast Iron and SnapLogic. By the time I joined Salesforce Industries, I knew the enterprise integration landscape well. Integration platforms (ETL and iPaaS) are incredibly capable. They connect virtually any system to any other system, support hundreds of connectors, and provide powerful transformation capabilities. They solve an enormous range of enterprise integration challenges—and they solve them well.

    I left Salesforce after nine amazing years, but I stayed closely connected to the ecosystem. I continued attending Dreamforce and following IdeaExchange, community discussions, and industry conversations.

    One theme kept surfacing:

    Data integration was slowing down Financial Services Cloud implementations.

    At first, I was confused.

    The integration technology already existed.

    So what was the real problem?

    I soon realized I was asking the wrong question.

    The biggest challenge wasn’t how to move data—it was capturing and productizing the implementation knowledge behind it.

    Take a typical Financial Services Cloud (FSC) implementation at a bank. One person understands the core banking system—whether it’s FIS, Fiserv, Temenos, or another platform. Someone else understands FSC’s data model. Another person knows how to configure and use the integration platform. The knowledge that connects those worlds—field mappings, business rules, and data fixes—is assembled for that specific implementation, but is rarely packaged in a reusable form for the next customer.

    The next implementation team often starts from scratch.

    That was the insight that changed the way I think about enterprise integrations.

    Many enterprise applications repeatedly connect to the same systems.

    Core banking systems and FSC are a good example.

    That led me to a simple question.

    What if enterprise applications came with purpose-built integrations for the systems they connect to most?

    Some integration patterns are repeated so frequently that they deserve to be productized.

    Salesforce has built an incredible suite of products and an equally incredible partner ecosystem. I saw an opportunity to contribute to that ecosystem by building Salesforce-native integrations that feel like a natural extension of the platform.

    We believe repeatable integration patterns shouldn’t require repeated implementations.

    Once I became convinced this was worth pursuing, I also knew there were people who understood parts of the problem better than I did. I sought guidance from a former SVP of Engineering at MuleSoft to help shape our thinking around enterprise integration. I also brought on a former SVP from FIS to ensure we were grounded in real-world core banking knowledge. Throughout the product’s development, we worked closely with the Salesforce Financial Services Cloud team to validate ideas, refine priorities, and ensure the product complemented the Salesforce ecosystem.

    That idea became DataIAm for FSC.

    Instead of asking every implementation team to recreate similar field mappings, data fixes, and synchronization logic, we built those assets into the product. Customers begin with prebuilt assets that dramatically improve time-to-value. Where their requirements differ, they can configure and extend them instead of starting with an empty project.

    We also made a few deliberate design decisions.

    First, we built the solution entirely on Salesforce. DataIAm for FSC runs inside the customer’s Salesforce org. No additional middleware. No external infrastructure to manage.

    Second, we built the user experience using Salesforce Lightning Design System (SLDS 2) because we believe partner products should feel like Salesforce.

    Finally, we made pricing part of the product design. Affordable pricing wasn’t an afterthought—it was one of the original design goals.

    Our goal was to solve one specific implementation challenge exceptionally well.

    Why did we start with the core banking use case for Financial Services Cloud?

    Because the problem was well understood and highly repeatable.

    Every bank is different, but many of the foundational integration patterns are remarkably similar. That made core banking integration the ideal use case to prove that implementation knowledge can itself become a product.

    FSC is only the beginning. Salesforce Industries includes many industry-specific clouds, and we believe the same philosophy can help accelerate implementations across many of them.

    We believe many enterprise applications can benefit from purpose-built, Salesforce-native integrations that eliminate repetitive implementation work while preserving the flexibility customers expect from the Salesforce platform.

    Looking back, building the software turned out to be the easy part. The real challenge—and ultimately the real product—was capturing years of implementation knowledge and making it reusable for every customer that followed.

    Whether we’re helping a Salesforce Admin import a spreadsheet with DataIAm Fix & Load or helping a bank connect its core banking system to Financial Services Cloud with DataIAm for FSC, our mission remains the same.

    Make Salesforce data effortless.

    To learn more about DataIAm visit: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • AI-Ready Financial Data

    AI-Ready Financial Data

    AI-Ready Data for Financial Services

    Financial institutions are investing heavily in AI to improve credit risk assessment, AML investigations, and Know Your Customer (KYC) reviews. But AI is only as effective as the data it receives.

    Salesforce Financial Services Cloud (FSC) becomes significantly more valuable when it contains not only CRM data, but also customer, account, loan, relationship, and transaction data from the bank’s core banking system. That richer, standardized view gives Salesforce Agentforce, workflows, analytics, and users far better context for making decisions.

    DataIAm for FSC helps establish that foundation by bringing core banking data into Financial Services Cloud using prebuilt field mappings, configurable data fixes, and Salesforce-native synchronization.

    Three examples illustrate why this matters.

    1. Credit Risk Assessment and Loan Processing

    Credit risk decisions depend on information that often resides across multiple systems—loan applications, customer profiles, collateral records, payment history, financial statements, and the core banking platform.

    When that information is fragmented, underwriters spend valuable time gathering context before they can evaluate risk.

    DataIAm for FSC brings core banking data into Financial Services Cloud using prebuilt mappings and configurable data fixes, creating a more complete customer and financial profile inside Salesforce.

    Once this richer data foundation exists, organizations can build Agentforce experiences and Financial Services Cloud workflows that assist underwriters by summarizing customer context, surfacing relevant information, recommending next steps, or helping prioritize work queues.

    Financial Services Cloud capabilities such as Action Plans, borrower relationships, householding, underwriting workflows, and document management integrations become more valuable when supported by complete and standardized data.

    Industry case studies have demonstrated significant improvements in lending efficiency when AI is combined with well-structured data and workflow automation, although results vary by institution and implementation.

    2. AML and Suspicious Activity Reviews

    AML investigators depend on accurate customer, household, account, and relationship information to determine whether an alert represents genuine suspicious activity or simply lacks sufficient context.

    Incomplete or inconsistent customer data increases manual investigation effort because analysts must retrieve information from multiple systems before making a decision.

    DataIAm for FSC enriches Financial Services Cloud with customer and relationship information from the core banking system, helping create a more complete view of each customer.

    With that richer context available in Salesforce, organizations can build Agentforce experiences that summarize customer relationships, highlight relevant activity, assist investigators during case reviews, and support more informed decision-making.

    Leading practices continue to include human review, governance, model validation, confidence thresholds, and comprehensive audit trails.

    3. Customer Onboarding and KYC Verification

    Customer onboarding and Know Your Customer (KYC) processes depend on accurate identity, household, account, and relationship information.

    By synchronizing core banking data into Financial Services Cloud, DataIAm for FSC provides a stronger foundation for onboarding workflows, customer profiles, and case management.

    Organizations can combine this trusted data with identity verification providers, sanctions screening, watchlist services, and Agentforce to streamline onboarding while maintaining appropriate human oversight.

    Financial Services Cloud capabilities such as householding, identity resolution, customer profiles, and case management become significantly more valuable when supported by complete and standardized customer data.

    Industry case studies have reported meaningful reductions in manual review effort through workflow automation and AI-assisted onboarding, although results depend on institutional processes, regulatory requirements, and risk policies.

    Clean Data Is the Foundation, Not the Afterthought

    Credit risk, AML, and KYC are different business processes, but they share one common dependency:

    Reliable data.

    Financial Services Cloud, Agentforce, analytics, and workflow automation all become more valuable when customer and core banking information is complete, standardized, and trustworthy.

    That’s where DataIAm for FSC fits.

    Rather than replacing AI, Financial Services Cloud, or enterprise integration platforms, DataIAm for FSC enriches Financial Services Cloud with trusted core banking data using prebuilt field mappings, configurable data fixes, and Salesforce-native synchronization.

    The result is a stronger data foundation that enables organizations to build more effective AI experiences, automate business processes, and help teams focus on the work that requires human judgment.

    Anshuman Sindhar

    Anshuman Sindhar General Manager, Industry Verticals DataIAm

  • Turning banking data into immediate customer value

    Turning banking data into immediate customer value

    The Competitive Advantage of Real-Time Banking Data

    Modern banking increasingly depends on real-time access to core banking data inside customer relationship management (CRM) systems including Salesforce Financial Services Cloud (FSC).

    Think of a common scenario in commercial banking.

    A relationship manager receives a call from a business client asking about expanding their line of credit. In many banks, answering this question requires pulling reports from several systems — core banking, treasury platforms, and credit systems.

    By the time the data is gathered, the conversation has stalled.

    When core banking transaction data is activated inside CRM systems, relationship managers can deliver personalized financial insights during live customer conversations. Unified customer data inside their CRM system changes the conversation immediately when relationship managers are able to see customer data such as:

    • recent transaction patterns
    • current credit utilization
    • seasonal cash-flow cycles

    Instead of gathering information, relationship managers begin solving customer problems immediately.

    That shift — from reactive processing to proactive advisory — is where modern banks win customer loyalty.

    Mid-Sized Banks Must Compete Differently

    Many regional and mid-sized financial institutions are investing in connecting core banking systems to CRM platforms in order to compete with larger banks on customer insight rather than physical scale.

    Large banks can invest billions of dollars expanding branch networks and building national brand recognition. In a recent interview, Bill Demchak, CEO of PNC Bank, discussed PNC Financial Service strategy of expanding its branch footprint and targeting 7–8% market share in major metropolitan areas to remain competitive.

    Few regional or mid-tier institutions can match that level of capital investment or wait through the long timelines required to build physical market presence. Instead, smaller and mid-sized banks win on speed, responsiveness, and relationship depth. And for that, relationship managers must be able to understand a client’s financial patterns immediately—cash flow trends, credit utilization, and transaction activity early in customer conversation. That advantage depends on infrastructure that brings core banking data directly into customer engagement platforms including Salesforce Financial Services Cloud.

    Connecting Core-banking to CRM: Challenges and Solutions

    Core banking systems such as FIS, Fiserv, and Jack Henry were built for reliable transaction processing—not for real-time analytics or CRM data activation. As a result, banks must transform raw transactional data into analytics-ready (and AI-ready) customer insights before it can be used effectively.

    At a high level:

    1. Core banking systems serve as systems of record for account and transaction data
    2. DataIAm for FSC, a data processing platform natively integrated with Salesforce FSC, connects core banking systems to FSC—enabling seamless data extraction
    3. Extracted data is automatically fixed to align with FSC data types, formats, and validation rules
    4. Clean data is mapped and loaded into FSC with built-in error monitoring

    Once loaded, FSC activates this data for relationship managers—powering 360-degree customer profiles and enabling AI-ready data for Salesforce Agentforce.

    DataIAm fro FSC fixes data from core banking systems to align with data types and data validations in Salesforce FSC before mapping and loading it.

    Responsible Data Activation

    As banks activate more client financial data inside CRM systems, the challenge is not only speed—it is data governance.

    Financial institutions need to ensure that customer data is used within strict privacy, security, and regulatory boundaries. Data governance frameworks, access controls, and auditability are essential to ensure that insights are delivered responsibly.

    Salesforce Financial Data Cloud architectures incorporate data access controls and PII protection to ensure responsible use of customer financial data.

    Salesforce Data 360 Is Now a Front-Office Strategy

    Customer 360 has traditionally been treated as a back-office IT initiative. Today, it is a core driver of customer experience.

    Banks that activate financial data in real time—or near real time—equip relationship managers to deliver proactive, informed advice in the moment. Conversations shift from reactive responses to personalized, insight-driven engagement.

    And in an environment where every interaction matters, the institutions that understand customer financial patterns first are the ones that earn—and keep—the relationship.

    DataIAm for FSC brings this to life by keeping core banking systems and CRM platforms continuously in sync—transforming raw financial data into trusted, actionable insights for relationship managers, directly within Salesforce Financial Services Cloud (FSC).

    Anshuman Sindhar

    Anshuman Sindhar General Manager, Industry Verticals DataIAm

  • History of data loaders for Salesforce

    History of data loaders for Salesforce

    When Salesforce admins or analysts need to import or export data, the first question is usually: Which Salesforce data loader should I use?

    For years, the ecosystem has been dominated by Salesforce Data Loader and MuleSoft dataloader.io, with tools like Jitterbit Salesforce Data Loader and Informatica Data Loader also available. These tools are familiar and have served the community well, but they haven’t kept pace with the needs of modern Salesforce users—they rely heavily on spreadsheets, can’t automatically fix bad data, and haven’t seen major updates in years.

    The good news: the market for Salesforce data loaders is huge. There’s room for multiple tools to succeed, each serving different types of users. DataIAm Fix & Load is a modern alternative designed specifically for admins and analysts who want speed, accuracy, and automation in one AI-powered tool.


    Salesforce Data Loader: An Engineer’s Side Project

    Salesforce Data Loader was originally built by an engineer as a side project. It’s a Java-based desktop app, now at v64, but visually and functionally it looks much like its earliest versions.

    Why admins still use it: it’s free and “good enough” for very basic Salesforce imports and exports.

    The problems:

    • No meaningful enhancements in years.
    • Bugs often unresolved.
    • Runs locally on users machine as a Java app.

    MuleSoft dataloader.io: A Marketing Project

    MuleSoft dataloader.io grew into the most popular alternative to Salesforce Data Loader, but it wasn’t engineering-led—it was launched by MuleSoft’s marketing team to funnel users into their expensive Anypoint platform.

    Signs of stagnation:

    • Last announced support for Salesforce API was v37 (Feb 2018). Current Salesforce API is v64.
    • A release announcement titled, “dataloader.io 1.0 has been released!”, is (likely incorrectly) dated Feb 14, 2024.
    • Last release notes were posted in January 2022 – over 2.5 years ago.
    • The product demo video were posted 10 years. 
    • IdeaExchange requests with hundreds of votes—like “Restrict picklist values for a standard field” (submitted in 2017, with 549 votes)—remains unresolved.
    • In 2022 MuleSoft lowered the cap on Free plan from 50,000 to 10,000 rows per month.

    And if that weren’t enough, dataloader.io Enterprise plan now runs $299 per user per month—with no team discounts.


    Jitterbit Salesforce Data Loader: Free but Forgotten

    Jitterbit Data Loader is only partially cloud-based as it still requires a local engine. That means admins must keep their machines running for scheduled jobs. Support is minimal (community-only), and macOS version is no longer updated.


    Informatica Data Loader: Moved On

    Informatica has pivoted to data warehouses and lakehouses like Snowflake and Databricks. A Salesforce-specific loader is no longer their priority.


    Why DataIAm Fix & Load Is Different: Power of AI

    DataIAm was built exclusively for Salesforce users who want more than just a data loader. It fixes errors automatically before loading, saving admins time and reducing mistakes

    Key Differentiators

    • Fix & Load: Automatically repair CSV structure issues, invalid picklist values, missing Record IDs, inconsistent date formats, abbreviated currency values, and more.
    • Actively Listening: We monitor IdeaExchange, Reddit, and LinkedIn. Features Salesforce admins begged MuleSoft for are already in DataIAm Fix & Load v1—for example, catching invalid picklist values.
    • Urgency & Focus: 100% dedicated to Salesforce data management. No side projects, no marketing funnels. Requests don’t sit ignored. Direct line: support@dataiam.com.

    Feature Comparison: DataIAm Fix & Load vs dataloader.io

    Fix & Load’s full Salesforce data loader feature comparison is available here: Compare Capabilities.

    Highlights of AI-powered features you won’t find in dataloader.io:

    • Fix file structure: Split single columns e.g., Address → Street, City, State, Zip.
    • Map fields by values: Automatically fix missing or incorrect headers by analyzing the values in the column before mapping.
    • Validate picklists: Flag and fix invalid picklist values before upload.
    • Remove inconsistencies: Standardize addresses, phone numbers, dates, and currency formats.
    • Fetch missing IDs: Auto-fill missing Salesforce Record IDs (for Update and Upsert jobs).
    • Smart Lookup: VLOOKUP-style matching between Salesforce objects and your file from within the app.
    • Preview data: See fixed data before upload.
    • Restore/Undelete: Recover deleted Salesforce records.
    • High capacity, low cost:
      • Freemium 100k rows ← 10x more capacity than dataloder.io
      • Enterprise $39/month for unlimited records ← 7x cheaper than dataloader.io

    The Bottom Line

    The first generation of Salesforce data loaders were side projects, marketing tools, or afterthoughts. They’ve been stagnant for years, frustrating Salesforce admins and analysts.

    DataIAm Fix & Load is different. Built for 2025 and beyond, it:

    • Uses AI to fix and load data
    • Eliminates manual data cleansing in spreadsheets
    • Saves admins and analysts hours every week

    If you want faster, smarter, and more reliable Salesforce data loading tool, start with the DataIAm Fix & Load, Freemium plan for $0 and experience AI-powered loading firsthand.


    To learn more about DataIAm visit: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • Be different! And win!

    Be different! And win!

    Most founders think they need the perfect résumé, the right connections, or the proven playbook to win.

    But in 1983, a 61-year-old farmer proved that sometimes the unconventional path changes everything.

    The Race No One Expected Him to Finish

    The race was brutal: 544 miles from Sydney to Melbourne. Elite ultramarathon runners—half his age—lined up, trained and sponsored, ready for glory.

    Then came Cliff Young. A 61 years old potato farmer in overalls and gumboots. No coach, no strategy, no special gear. Just years of chasing sheep across thousands of acres… and a belief in himself.

    The crowd laughed when they saw him. He didn’t even look like a runner.

    The Shuffle That Changed Everything

    When the gun fired, Cliff set off with a strange, awkward gait. Reporters called it the “Young Shuffle”. Runners disappeared into the distance while Cliff lagged behind.

    But while the elites followed tradition—running 18 hours, sleeping 6—Cliff kept shuffling. Through the night. Through the pain. Through every mile.

    By not knowing the “rules,” he broke them.

    By not stopping, he won.

    Cliff crossed the finish line 10 hours ahead of the the athlete in the 2nd position. A farmer in gumboots, rewrote the history of ultramarathons.

    What Startups Can Learn from Cliff Young

    1. Credentials don’t decide outcomes– Cliff had no résumé that said “elite athlete”. Founders don’t need one either.
    2. Ignorance can be freedom He didn’t know the “right” way to run a ultramarathon. That ignorance became his edge.
    3. Persistence beats pedigree Endless shuffling outlasted the best-trained runners. Startups win the same way—by refusing to stop.

    Why This Inspires Us at DataIAm

    At DataIAm, we’re building with the same mindset.

    We don’t follow the playbook of traditional data tools—complex, bloated, built only for engineers. Instead, we’re taking a different path: making Salesforce data loading and fixing radically simple, for anyone.

    Just like Cliff’s shuffle, it may look unconventional. But we believe it’s the winning strategy.


    Sometimes, it’s the potato farmer in gumboots who rewrites the rules of the race.

    For startups, that’s the reminder: the path no one expects may be the one that wins.

    👉 What’s your “Young Shuffle”?

    To learn more about DataIAm visit: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • Product managers don’t control the product — we can only aspire to intervene

    Product managers don’t control the product — we can only aspire to intervene

    I never set out to study architecture engineering. I stumbled into architecture almost by accident. But once I was there, I was hooked.

    It was the perfect intersection of engineering and art. I can still see my professor at the chalkboard sketching a design in seconds, narrating an architectural style as if he were pulling it straight out of thin air.

    Architecture wasn’t just about lines on paper. In materials engineering, I learned how the right choices could balance insulation, sustainability, and aesthetics. In structural engineering, I discovered the art of the possible: Would this design hold? Could it withstand a flood or an earthquake?

    I felt found.

    But life had other plans. I had to switch colleges (that story for another day), and the new one didn’t offer architecture. So, I enrolled in computer engineering instead. Studying programming, data structures, databases, software engineering — the whole enchilada.

    From there, my career journey carried me from writing backend code, to delivering customizations in professional services, and ultimately to product management — my home for the past two decades. I fell in love with the craft of product management, but my fascination with architecture never disappeared; it lingered quietly in the background.

    YES IS MORE

    Recently, while trying to clear my head before diving into my latest project — DataIAm  — I picked up a book by Danish architect Bjarke Ingels, titled YES IS MORE. I thought it would be an escape, something unrelated to work. Turns out, it was the opposite: an architecture book that spoke directly to my product management soul.

    One page stopped me in my tracks:

    “Architecture is never triggered by a single event, never conceived by a single mind, and never shaped by a single hand…. We architects don’t control the city — we can only aspire to intervene.”

    I read it once as an admirer of architecture. Then I read it again as a product manager. And I realized: the same is true of products.

    Slightly reworded, it could have read:

    A product is never triggered by a single event, never conceived by a single mind, and never shaped by a single hand…. We product managers don’t control the product — we can only aspire to intervene.”

    That hit me.

    The Architecture of Products

    In architecture, you balance the technical (Will the structure hold up?) with the artistic (Will people feel inspired, connected, at home here?).

    Product management, it turns out, is no different. It’s half engineering and half art. It’s about building consensus — not by simply creating what everyone already agrees on, but by bridging the gap between what people like, what they want, what they think they need, and what they’ll only realize they love once they have it.

    Over the last two decades, I’ve had the privilege of designing and launching many products. But as I was shaping DataIAm Fix & Load , the philosophy of YES IS MORE gave me a new lens. Had I not read that book, the design and build of DataIAm app and website would have looked very different. What seemed like an “unrelated” book turned out to be deeply related, reinforcing that products — like buildings — are about creating spaces where people belong, thrive, and say: “This is exactly what I didn’t know I needed.”

    YES IS MORE (than architecture)

    Bjarke Ingels titled his book YES IS MORE as a playful response to Mies van der Rohe’s mantra “Less Is More” — a phrase we product managers often find ourselves saying, too.

    But in product management, YES IS MORE isn’t about saying yes to everything. It’s about saying yes to bold ideas — the ones that connect engineering with art, push boundaries while pulling people in.

    That’s why I’ve come to believe:

    Software product managers are just building architects in disguise.

    We may not shape skylines, but we shape the digital spaces where people live parts of their lives. And just like great architecture, the best products don’t just meet needs — they surprise us with a sense of belonging we didn’t know we were missing.


    To learn more about DataIAm visit: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • DataIAm Fix & Load: PR/FAQ

    DataIAm Fix & Load: PR/FAQ

    The “PR/FAQ” documents are fictitious press releases. See details:

    This document outlines the vision, problem, and solution
    behind the founding of DataIAm.

    It is intended to be publicly shared to explain what we’re
    building and why it matters.

    Inspired by Jeff Bezos’ practice at Amazon, this is the
    fictitious press release we wrote in June 2024—
    before writing a single line of code.

    The product became publicly available in February 2025.


    📣 Press Release

    DataIAm Launches AI-Powered Salesforce Data Loader

    San Francisco, CA — February 24, 2025 — Today marks the launch of DataIAm Fix & Load, an AI-powered data loader purpose-built for Salesforce. Designed for Salesforce Admins and data professionals alike, DataIAm Fix & Load brings AI intelligence to the data loading process—automatically detecting common issues, suggesting intelligent fixes, and ensuring clean data is loaded into Salesforce.

    Salesforce Admins have long been frustrated that data loaders are just that—loaders. They’re forced to manually fix broken or messy data, often in spreadsheets, before even attempting to import it. Fix & Load reimagines this workflow by providing an intelligent, supportive interface that streamlines both data cleanup and loading.

    “We’re reimagining the data loading experience from the ground up,” said Zeb Mahmood, co-founder of DataIAm. “No more manual cleanup. Just upload your messy CSV—and let our AI fix and load it for you.”

    Zeb brings over nine years of product leadership experience at Salesforce and two decades of building data platform products. His deep understanding of enterprise applications and integration pain points inspired the creation of DataIAm.

    Customer feedback has already been enthusiastic.

    “I used to spend hours cleaning data in Excel just to get it ready for a Salesforce import. Now I just toss the CSV into Fix & Load, and it does the fixing for me. What used to be a painful chore is now a quick, confident step,” said Jessica Lin, Salesforce Admin at AcmeTech.

    “Having clean, accurate data in Salesforce is a game-changer for our pipeline health and forecasting accuracy. Fix & Load gives me confidence in the numbers we’re reporting upstream,” said Raj Mehta, CRO at Cresthill Systems. “Once the data is in Salesforce, it’s 100x more expensive to clean. DataIAm Fix & Load is our gatekeeper for good data!”

    This ability to save hours of manual cleanup work is where DataIAm Fix & Load delivers its biggest value. Admins can now focus on delivering business value instead of wrangling spreadsheets and VLOOKUPs.

    Try DataIAm Fix & Load for free at https://dataiam.com—no credit card required. You can sign in using your Salesforce credentials (SSO supported) and get started in minutes.


    Key Features

    Here’s what sets DataIAm Fix & Load apart from traditional data loaders:

    • Auto-detects target object and fields based on your CSV—even if headers are missing or incorrect
    • Fixes malformed CSVs, like addresses crammed into a single column
    • Suggests intelligent fixes for invalid picklist values, incorrect formats, and more
    • Fetches missing Record IDs using match fields—no need for Excel VLOOKUPs
    • Normalizes values based on field type (e.g., for Revenue field, $100M → 100000000.00)
    • Lets you preview fixes before loading into Salesforce
    • Supports SSO login with your Salesforce ID—no extra logins to manage
    • Free to use, with no credit card required

    FAQ

    What is DataIAm Fix & Load?

    DataIAm Fix & Load is a Salesforce data loader powered by AI. Unlike other data loaders, it helps users fix the data before loading—no engineering skills required.

    Who is it for?

    DataIAm Fix & Load is designed for Salesforce Admins and non-engineering users who regularly deal with data import/export tasks, as well as for data professionals who want to save time on cleanup. Our primary persona is “Alex Smith,” a Salesforce Admin who juggles multiple data tasks without writing code.

    Why are you building this?

    Because current tools are just loaders. But in reality, every CSV is messy in its own way, and the Admin is often left to clean up that mess before loading the data. We believe the loading experience should have fixing of data built-in; it should be intelligent, contextual, and supportive—just like a good assistant. And more importantly, it should save users hours of spreadsheet wrangling and guesswork every time they prepare a file.

    Fixing data before it enters Salesforce is not just more efficient—it’s essential. Once bad data is loaded, the cost to detect and fix it skyrockets. Broken flows, inaccurate dashboards, failed automations, and degraded user trust all stem from poor data hygiene. In the age of AI, accurate and timely data is everything—because AI is only as good as the data it learns from and operates on.

    What’s next?

    Salesforce is the first ecosystem; we’ll be building AI-powered data loaders for ServiceNow, NetSuite, Workday, and many more.


    To learn more or sign up: https://dataiam.com

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • Case of missing Record IDs

    Case of missing Record IDs

    If you’ve ever been asked to mass update Salesforce records, you’ve likely run into The Record ID Problem.

    It goes like this:

    • A business team sends you a spreadsheet full of updated Salesforce data
    • You’re the Salesforce Admin or Analyst expected to upload it
    • But the spreadsheet? It doesn’t have Record IDs—and Salesforce Bulk API requires them for updates

    Why Spreadsheets Are Often Missing Record IDs

    People love working in Excel or Google Sheets. It’s fast, flexible, and familiar.

    Here’s a real-world example:

    A Marketing Manager downloads lead records from Salesforce, enriches them with firmographic data from a third-party source, and sends you the updated spreadsheet. Now they want you to push those updates back to Salesforce.

    But there’s a problem: the Record IDs are missing.

    To fix this, most Salesforce Admins have to:

    • Export the Lead object from Salesforce, including Record IDs
    • Manually insert the retrieved IDs into the original file i.e. use Excel’s VLOOKUP to match on a unique field like Email or Cell Phone

    This problem is so common that Salesforce Support even published a video tutorial: How to Prepare Your CSV File Using Vlookup in Excel

    How DataIAm Fix & Load Solves It

    Let’s say you get a spreadsheet from Marketing with updated Lead data—but no Record IDs.

    Here’s what happens in DataIAm Fix & Load, our AI-powered Fix & Load tool:

    1. Create an Update job and upload the spreadsheet 
    2. Fix & Load’s AI auto-detects the target object e.g., Lead
    3. Next, choose an option:
      • “CSV has IDs” , or
      • “Fetch IDs from Salesforce”
    4. If you choose to fetch IDs, simply select a match column (e.g., Cell Phone), and Fix & Load will retrieve and insert the corresponding Record IDs directly into your file.

    During the match process, DataIAm Fix & Load flags:

    • Multiple ID rows – where the match column returns more than one record in Salesforce
    • Missing ID rows – where no matching record is found

    Then you simply run the job. Done. ✅

    Optionally, DataIAm Fix & Load lets you:

    • “Preview Record IDs” and download the enriched “CSV with IDs”.
    • “Download problem rows” file with multiple or missing IDs for further review.
    • On the “Data Fixes” screen, AI automatically identifies and corrects common issues. For example: If a column like Revenue contains non-numeric formats (e.g., "$100M" or "USD20,000"), they are normalized to standard numeric values (100000000.00 and 20000.00).

    Isn’t that magical! R.I.P., Excel VLOOKUP!


    TL;DR

    Salesforce Bulk API requires Record IDs to update records. But spreadsheets from business users often don’t include them. DataIAm Fix & Load fixes that—automagically.

    ✅ Fetches missing Record IDs
    ✅ Cleans messy spreadsheets before loading
    ✅ Handles edge cases e.g., rows that match multiple IDs


    Try It Free

    👉 dataiam.com
    📩 Or email our co-founder Zeb at TryNewThings@dataiam.com for a live walkthrough.


    About the Author

    Zeb Mahmood has spent his career unlocking business value by moving, fixing, and loading data—first as an engineer, then as a product leader, and now as a cofounder.

    With 2 decades in product management, 9 years at Salesforce, and hands-on experience in early-stage startups, he’s learned a simple truth: data is the lifeblood of every business. But when it’s messy or trapped in spreadsheets, it can’t drive impact.

    That’s why Zeb cofounded DataIAm — a Fix & Load AI built for Salesforce Admins and data handlers who just want their data to work. No frustration. No failed imports. Just clean, reliable data that loads seamlessly into Salesforce and delivers results.

    Zeb believes great products don’t win on tech alone — they win through empathy. Empathy for users, buyers, partners, and the people building the product every day.

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm

  • Now querying: Related objects

    Now querying: Related objects

    Let’s be honest—querying related objects in Salesforce isn’t exactly fun.

    If you’ve ever tried pulling a report of Opportunities along with Account names and the Owners’ aliases, you’ve probably ended up with multiple browser tabs open for SOQL dot notation help, a couple of manual VLOOKUPs, and maybe even a silent prayer.

    We’ve been there. So we made it better.

    We’re thrilled to announce a major upgrade to our Extract functionality (a.k.a. Salesforce Query Builder) in DataIAm Fix & Load:

    You can now query related objects in Salesforce—with just a few clicks!

    What Are Related Objects in Salesforce?

    Salesforce data is stored in a web of related objects—like linked database tables. A few examples:

    • A Contact belongs to an Account
    • An Opportunity is tied to both an Account and an Owner
    • A Case links to a Contact and an Account

    Also see: Object Relationships Overview by Salesforce


    How to Query Related Objects with DataIAm Fix & Load

    Until now, if you wanted to export data with related fields, you had to export one object at a time, merge them in Excel using VLOOKUP, and hope nothing breaks.

    But now you can: choose your base object, then select related fields across related objects—visually and with zero SOQL (yes, no guessing the dot-notation syntax).

    ✅ Select any standard or custom Salesforce object
    ✅ Browse related objects and pick the fields you want
    ✅ Preview your result set before full extraction

    It’s clean, intuitive, and designed for Salesforce admins, analysts, and consultants who just want the data—without the SOQL and spreadsheet drama.

    ⚠️ Like native SOQL and most third-party tools, you can go up the relationship chain — from child to parent (e.g., Opportunity → Account → Owner). However, you can’t yet go down (e.g., Account → all Contacts). We’re working on a way to support that for you — even though SOQL itself doesn’t natively allow it.


    Example: Query Related Salesforce Data

    Let’s say your manager asks for a list of open Opportunities that includes:

    • Opportunity Name
    • Account Name
    • Owner’s Alias

    In DataIAm Fix & Load, just:

    1. Select the Opportunity object and the Name field
    2. From Related Objects:
      • Choose Account → Name
      • Choose Owner → Alias
    3. See the auto-generated SOQL:
      SELECT Name, Account.Name, Owner.Alias FROM Opportunity
    4. Preview result set → Run job → Done!

    Also see the blog post: Visual Query Builder


    Modern Fix & Load vs. Clunky Old Data Loaders

    With this latest enhancement, DataIAm Fix & Load is now more functionally capable than any leading data loader in the market. (Not bragging — just stating the facts.)

    Unlike traditional tools, DataIAm Fix & Load includes smart, AI-powered capabilities like:

    ✅ Flagging and fixing invalid picklist values
    ✅ Fetching missing Record IDs
    ✅ Correcting inconsistent data formats
    ✅ Previewing (and downloading) cleaned data before loading

    Want to see how DataIAm Fix & Load compares to Salesforce Data Loader (desktop) and MuleSoft dataloader.io? Check out our side-by-side feature comparison — a.k.a. the “truth table” — right here: https://dataiam.com/#data-loaders-side-by-side 


    TL;DR

    You can now query related objects in Salesforce using the DataIAm Fix & Load SOQL Query Builder—a visual, no-code way to quickly extract Salesforce data from related objects.

    No SOQL scribbling → SOQL with dot notation is generated for you

    No VLOOKUP dance → Select related fields visually

    No trial-and-error guessing → Preview the result set before exporting


    Try it FREE at: dataiam.com
    Or email our co-founder, Zeb, at TryNewThings@dataiam.com for a live walkthrough.
    We’d love to hear your use case!


    About the Author

    Zeb Mahmood has spent his career unlocking business value by moving, fixing, and loading data—first as an engineer, then as a product leader, and now as a cofounder.

    With 2 decades in product management, 9 years at Salesforce, and hands-on experience in early-stage startups, he’s learned a simple truth: data is the lifeblood of every business. But when it’s messy or trapped in spreadsheets, it can’t drive impact.

    That’s why Zeb cofounded DataIAm — a Fix & Load AI built for Salesforce Admins and data handlers who just want their data to work. No frustration. No failed imports. Just clean, reliable data that loads seamlessly into Salesforce and delivers results.

    Zeb believes great products don’t win on tech alone — they win through empathy. Empathy for users, buyers, partners, and the people building the product every day.

    Zeb Mahmood

    Zeb Mahmood Co-Founder & CEO DataIAm