Benjamin Rogojan's LinkedIn Strategy…

Data engineers and analysts often under value the knowledge they have. Think about it. You've spent hours upon hours learning Python, SQL, how to build data warehouses and understanding the differen…

14211123 viral

Career Advice3 months ago

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Dear CEOs and Data VPs, Your data team doesn’t need more headcount or another data platform to find value from data. They need to be able to focus! Right now, they’re drowning in: - Random asks an…

1392641 viral

Data Strategy3 months ago

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I jumped on a call with a CTO, they had spent the past six months trying and failing to stand up their data stack. They were using SQL Server and SSIS and it just wasn't working. In fact, during one…

1213121 viral

Data Engineering3 months ago

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Running a successful data team is hard. You're often pressured to deliver quickly sometimes feeling as if you aren't given the proper amount of time to consider data modeling or quality. Other times…

731851 viral

Data Team Leadership3 months ago

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Behind every business-critical dashboard is three partially automated Lambda functions, a 2500-line SQL query written by someone who left three years ago, and four layers of BI calculations. Not to m…

652021 viral

Data Engineering3 months ago

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Running a successful data team is hard. There is so much FOMO-driven data strategy that the business wants to implement that it can be difficult to actually deliver what the business needs. They wan…

502661 viral

Data Strategy4 months ago

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Topics & Content Focus

Primary Topics

Pragmatic data leadership and business alignment (helping data leaders focus on what actually drives outcomes, prioritize, and say no to noise)Reducing technical friction in modern data stacks (simplifying pipelines, breaking out of legacy tools, making infrastructure manageable for small teams)Anti-hype, anti-FOMO data and AI strategy (critiquing shiny tools, Gartner-driven roadmaps, and misaligned investments)Career and income leverage for data professionals through consulting (monetizing expertise beyond employment, building data consulting careers and communities)

Secondary Themes

Data team operating models and prioritization frameworksTrustworthy, production-grade analytics and BI (testing, ownership, documentation)Tool selection and vendor sprawl in the modern data stackExecutive education on realistic expectations from data teamsCommunity-building among data leaders and data consultants

Industry Focus

Modern data infrastructure and analytics in B2B product companiesData leadership in tech-driven and SaaS-like environmentsData engineering and analytics consulting for small to mid-sized teamsCloud data warehousing and real-time pipelines in product-led businesses

Content Categories

Strategic thought leadership for data and business leadersNarrative case studies of broken vs. fixed data stacksCareer and business-building content for data professionalsEducational breakdowns of production-ready data practicesCommunity and program promotion (playbooks, groups, events)

Performance Insights

129%

Avg Engagement Rate

INCREASING

Performance Trend

Best Performing Topics

Data team focus and business alignment over headcount and toolsConcrete turnaround stories of broken legacy stacks migrated to modern cloud setupsCareer monetization and consulting paths for data engineers and analysts

Virality Signals

Exceptionally high comment counts on posts that promise community access and career leverage for data professionalsStrong resonance when calling out widely-felt pain (being undervalued, duct-taped dashboards, tool sprawl)Posts combining personal credibility (real client story) with clear transformation narratives tend to earn above-average engagement and sharing

Structure & Quality

260

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

8.5/10

Uniqueness Score

Common Hooks

Directly addressing executives or leaders with a contrarian claim (e.g., telling CEOs what they don’t actually need)Bluntly stating how hard or broken something is (“Running a successful data team is hard”, “Behind every business-critical dashboard is…”)Opening with a concrete, high-tension scene from a client engagement (failed hand-offs, systems breaking mid-call)Calling out industry-wide dysfunction like FOMO-driven strategies and tool sprawl

Common Endings

Soft CTA to join a niche community or playbook for deeper helpInvitation to comment to get access (comment-to-join loops)Prompt to submit questions for upcoming sessions or contentLink-out to a longer-form article for deeper implementation details

Value Delivery Methods

Reframing common data problems from a purely technical issue into a strategic and organizational focus challengeSharing specific implementation choices (e.g., migrating to cloud warehouse, focusing on two key datasets) rather than vague adviceEquipping data professionals with a mindset to value and monetize their expertise, not just execute ticketsEducating leaders on why their current expectations and behaviors (random asks, tool FOMO) sabotage data value

Formatting Style

Short paragraphs with frequent line breaks for readabilityBullet lists to enumerate pain points, realizations, and outcomesContrast structures (“You don’t need X. You need Y.”)Narrative arc: setup → problem → reframe/solution → outcomes → CTA

Audience & Tone

YES

Question Usage

0.8%

Response Rate

Detected Tone

Pragmatic operator with hands-on experience fixing real data messesRelatable expert who speaks plainly about complex systemsAnti-hype strategist pushing back against FOMO and buzzword-driven decisionsSupportive mentor to data professionals looking to increase their leverage and autonomysemi-formalfirst-person

Interaction Style

Two-sided: speaking to both executives and hands-on data practitioners, often mediating between their worldsCommunity-oriented, using comments as a gateway into private groups or deeper programsPrompt-driven, using questions to collect pain points and shape future content or sessions

Community Building Signals

Recurring promotion of specialized communities (Data Leaders Playbook, data consultants group)Using comment-to-join mechanics to seed ongoing conversations and move engagement off the feedPositioning content as the surface layer of a deeper ecosystem of resources, peers, and programs

Writing Style Patterns

Content Strategy

Hook: Directly addressing executives or leaders with a contrarian Tone: semi-formalCTA: Community invitations targeted at specific persona

Writing style breakdown

Core characteristics

Overall tone: professional but conversational, directed at a LinkedIn-style business audience.

Voice: authoritative, mentoring, and pragmatic, with a “been there, seen this many times” feel.

Style: direct, concise, and outcome-oriented, with an emphasis on business value and practical impact.

Emotional tone and energy

Energy level: medium-to-high.

- The posts often open with a strong, simple assertion or problem statement

Running a successful data team is hard.

Your data team doesn’t need more headcount…

Emotion: a mix of frustration with industry dysfunction (FOMO, shiny tools, duct tape systems) and optimism about solutions.

There is measured urgency, not panic; more “we need to fix this” than “the world is on fire.”

- Rhetorical questions to engage and pivot

So, how can you get things done and move your data team forward?

Who should i talk to next?

- Contrast and reversals

You don’t need another dashboard… You don’t need more people… You need clarity…

The reality is, tools won’t fix a broken business strategy. But the right tools…

Repetition for emphasis (especially “They want… They want…”, “You don’t need… You don’t need…”).

Concrete details from real work (CTOs, SQL Server, 2500-line queries, Lambda functions).

- Occasional mild humor / irony

Of course you should be using Snowflake, Bigquery And Databricks right?

Just enough duct tape to keep the business running.

- Uses simple, accessible metaphors

drowning in random asks

duct-taping SQL Server

technical friction

- Dominant perspective: second person (“you”) to speak directly to

CEOs, VPs, data leaders, data engineers/analysts.

- First person (“I”) and “we” appear when

Sharing personal consulting stories or decisions.

Generalizing about the industry (“we are still facing many of the same problems”).

- Often uses soft but direct guidance

If you are a data or a business leader who wants to… then the Data Leaders Playbook community is for you.

So why not come and chat with other data people in Denver!

- Imperatives are generally friendly, not aggressive

Please sign up and let me know…

Feel free to tag some friends in Denver!

So if you are interested in starting a consulting company, then feel free to comment below…

Benjamin Rogojan

Warm Analysis

Performance Overview

Top Posts by Engagement

Posting Patterns & Frequency

Best Performing Days

Best Performing Times To Post

Topics & Content Focus

Primary Topics

Secondary Themes

Industry Focus

Content Categories

Performance Insights

Best Performing Topics

Virality Signals

Structure & Quality

Common Hooks

Common Endings

Value Delivery Methods

Formatting Style

Audience & Tone

Detected Tone

Interaction Style

Community Building Signals

Writing Style Patterns

Content Strategy

Core characteristics

Emotional tone and energy

- The posts often open with a strong, simple assertion or problem statement

- Rhetorical questions to engage and pivot

- Contrast and reversals

- Occasional mild humor / irony

- Uses simple, accessible metaphors

- Dominant perspective: second person (“you”) to speak directly to

- First person (“I”) and “we” appear when

- Often uses soft but direct guidance

- Imperatives are generally friendly, not aggressive