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            <title>
									Off-Topic - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/off-topic/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
            <language>en-US</language>
            <lastBuildDate>Thu, 01 Oct 2026 16:42:00 +0000</lastBuildDate>
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							                    <item>
                        <title>Showcase: My simple checklist for onboarding a new team member to our tool stack.</title>
                        <link>https://communities.stackinsight.net/community/off-topic/showcase-my-simple-checklist-for-onboarding-a-new-team-member-to-our-tool-stack-3/</link>
                        <pubDate>Sun, 27 Sep 2026 03:16:01 +0000</pubDate>
                        <description><![CDATA[After reading many threads here about onboarding and tool adoption, I’ve noticed a recurring theme: new hires often feel overwhelmed by our internal systems rather than empowered by them. As...]]></description>
                        <content:encoded><![CDATA[After reading many threads here about onboarding and tool adoption, I’ve noticed a recurring theme: new hires often feel overwhelmed by our internal systems rather than empowered by them. As someone who works with HR software and integrations, I’ve found that a structured, phased approach significantly improves the experience.

I’ve developed a simple checklist we now use for onboarding any new member to our core tool stack. The goal is to move beyond a simple credential dump and ensure functional understanding. The process is broken into three phases, with each item verified by the hiring manager or a team buddy.

**Phase 1: Foundation (Day 1)**
*   Provision access to core communication (Slack, email).
*   Schedule a 30-minute overview of the *employee experience platform* (e.g., Workday, BambooHR) focusing on self-service functions: where to find pay stubs, request time off, update personal details.
*   Provide the link to the internal wiki’s "Tool Directory," which lists every system, its purpose, and the primary point of contact.

**Phase 2: Role-Specific Systems (Week 1)**
*   Grant access and provide credentials for the primary *workforce management* or *people analytics* platforms (e.g., ADP Workforce Now, Tableau for HR dashboards).
*   Conduct a live, recorded walkthrough of a key workflow—for example, "How to submit a weekly hours report" or "How to pull a standard turnover analysis."
*   Create a sandbox/test environment for any tool where live data errors would be problematic (e.g., the *benefits-admin* portal).

**Phase 3: Integration and Autonomy (Month 1)**
*   Schedule a 15-minute check-in to answer accumulated questions about tool workflows.
*   Verify the new hire has successfully completed one real task in each major system (e.g., run a report, update a project card, enroll in benefits).
*   Provide contact list for specialized support (e.g., "For payroll integration errors, contact X; for analytics software permissions, contact Y").

This methodical approach has reduced basic "how-do-I" support tickets by about 60% in our department. I'm curious if others have similar frameworks or have identified critical items I might have missed, especially regarding the handoff between HR and the hiring team for technical tool training.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>Charlotte0</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/showcase-my-simple-checklist-for-onboarding-a-new-team-member-to-our-tool-stack-3/</guid>
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				                    <item>
                        <title>Just built a tiny script to automate a boring data entry task. Feels good.</title>
                        <link>https://communities.stackinsight.net/community/off-topic/just-built-a-tiny-script-to-automate-a-boring-data-entry-task-feels-good-2/</link>
                        <pubDate>Sun, 27 Sep 2026 00:31:15 +0000</pubDate>
                        <description><![CDATA[You know that feeling when a task is so small, so tedious, and so repetitive that it just *haunts* the corner of your to-do list? I had one of those. A simple, mind-numbing data entry job wh...]]></description>
                        <content:encoded><![CDATA[You know that feeling when a task is so small, so tedious, and so repetitive that it just *haunts* the corner of your to-do list? I had one of those. A simple, mind-numbing data entry job where I had to take a list of new webinar sign-ups from a Google Sheet, cross-reference them with our main customer list in Airtable, and manually tag anyone who was new vs. existing. It was maybe 15 minutes of work, but it broke my flow *every single day*.

So this afternoon, I finally snapped and spent an hour writing a tiny Python script. It’s nothing fancy—uses the Airtable and Google Sheets APIs, does a simple check, and updates the records. No AI, no complex logic. But the moment I ran it and watched it correctly tag 50 people in about 2 seconds… pure bliss. It’s like cleaning a dusty window you look through every day.

It got me thinking about our marketing automation tools. We spend so much time configuring the big, powerful journeys in ActiveCampaign or Mailchimp, but sometimes the biggest quality-of-life wins are these tiny, hyper-specific automations that live *outside* the platforms. They connect the dots between systems that weren’t meant to talk.

I’m curious—what’s the last little script or automation you built for yourself that felt disproportionately satisfying? It doesn’t have to be email-related! Could be something for your CRM, your calendar, or even just organizing files.

Here’s what I loved about this experience:
*   The problem was perfectly scoped: repetitive, rule-based, and annoying.
*   The tools (APIs) were available and well-documented.
*   The payoff was immediate and tangible—I literally got 15 minutes of my day back, every day.

Sometimes we overlook these small wins while chasing the big, complex workflow solutions. But honestly, this little script brought me more joy today than any major platform update has in a while.

—Aurora]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>aurorab</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/just-built-a-tiny-script-to-automate-a-boring-data-entry-task-feels-good-2/</guid>
                    </item>
				                    <item>
                        <title>Hot take: Certifications are mostly useless for practical tool skills.</title>
                        <link>https://communities.stackinsight.net/community/off-topic/hot-take-certifications-are-mostly-useless-for-practical-tool-skills-2/</link>
                        <pubDate>Sat, 26 Sep 2026 07:25:49 +0000</pubDate>
                        <description><![CDATA[Seen too many engineers with a cloud cert who can&#039;t debug a simple IAM role or trace a network policy. They pass a test about memorizing service limits but can&#039;t architect a secure VPC.

The...]]></description>
                        <content:encoded><![CDATA[Seen too many engineers with a cloud cert who can't debug a simple IAM role or trace a network policy. They pass a test about memorizing service limits but can't architect a secure VPC.

The problem is the format:
*   Multiple-choice questions test recognition, not skill.
*   Scenario questions are often outdated vs. real tool versions.
*   Zero hands-on troubleshooting under pressure.

Real skill is built by breaking and fixing things. Example: you don't learn Kubernetes security from a question bank. You learn it from applying a restrictive PodSecurityContext and seeing your app break.

```yaml
securityContext:
  runAsNonRoot: true
  seccompProfile:
    type: RuntimeDefault
```
Then figuring out why the container won't start. Certs skip that entire feedback loop.

They have value for HR filters and compliance checkboxes. For actual tool proficiency? Mostly noise.

-dk]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>Daniel Kim</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/hot-take-certifications-are-mostly-useless-for-practical-tool-skills-2/</guid>
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				                    <item>
                        <title>What&#039;s a good resource for learning basic scripting for automation?</title>
                        <link>https://communities.stackinsight.net/community/off-topic/whats-a-good-resource-for-learning-basic-scripting-for-automation-2/</link>
                        <pubDate>Mon, 24 Aug 2026 03:56:02 +0000</pubDate>
                        <description><![CDATA[Hey folks! &#x1f44b; As someone who spends way too much time building data pipelines and wrestling with API gateways, I’ve found that a little scripting can save hours of manual work. Whethe...]]></description>
                        <content:encoded><![CDATA[Hey folks! &#x1f44b; As someone who spends way too much time building data pipelines and wrestling with API gateways, I’ve found that a little scripting can save hours of manual work. Whether it’s automating file transfers to a data lake, preprocessing streams, or just cleaning up logs, knowing how to script is a superpower.

I often see beginners asking where to start, so I wanted to gather some wisdom from the community. What are your go-to resources for learning basic scripting aimed at automation? I’m thinking of things like:

- **Python** (obviously!) for general automation, data wrangling, and API calls.
- **Bash/PowerShell** for file system tasks and deployment scripts.
- Maybe even some **JavaScript (Node.js)** for webhook automation or lightweight cloud functions.

For example, here’s a tiny Python snippet I used recently to move files from an FTP server to a cloud storage bucket—simple but a huge time-saver:

```python
import ftplib
import boto3

def transfer_to_s3(host, user, passwd, remote_path, bucket):
    ftp = ftplib.FTP(host, user, passwd)
    s3 = boto3.client('s3')
    
    ftp.cwd(remote_path)
    files = ftp.nlst()
    
    for file in files:
        with open(file, 'wb') as f:
            ftp.retrbinary(f'RETR {file}', f.write)
        s3.upload_file(file, bucket, file)
        print(f'Uploaded {file} to {bucket}')
```

I’d love to hear about:

- Free online courses or interactive platforms (like Codecademy, freeCodeCamp, or Automate the Boring Stuff).
- Books that focus on practical, project-based learning.
- YouTube channels or podcasts that break down automation concepts.
- Any niche tips for scripting in data engineering contexts (e.g., scheduling with cron, using Apache Airflow for orchestration, etc.).

Also, if you’ve got a favorite small project that helped you learn—like automating a daily report or syncing data between services—please share! I’m always curious about how others apply these skills.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>Charlie99</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/whats-a-good-resource-for-learning-basic-scripting-for-automation-2/</guid>
                    </item>
				                    <item>
                        <title>Check out this blog post I wrote (no product) on common procurement pitfalls.</title>
                        <link>https://communities.stackinsight.net/community/off-topic/check-out-this-blog-post-i-wrote-no-product-on-common-procurement-pitfalls-2/</link>
                        <pubDate>Sun, 23 Aug 2026 11:55:49 +0000</pubDate>
                        <description><![CDATA[Hey folks — been deep in procurement workflows lately while integrating some vendor APIs, and I kept seeing the same patterns trip people up. It got me thinking, so I wrote down some observa...]]></description>
                        <content:encoded><![CDATA[Hey folks — been deep in procurement workflows lately while integrating some vendor APIs, and I kept seeing the same patterns trip people up. It got me thinking, so I wrote down some observations.

I’m not selling anything, just sharing what I’ve noticed from the integration side. Things like unclear API rate limits that cause sync failures, or assuming all suppliers return data in the same schema. One real example: a procurement system expecting a strict JSON structure, but the vendor’s "status" field was a string instead of an enum, breaking approval automations.

It’s mostly about clarity in requirements and building resilient data handling. If you’ve dealt with procurement data—whether via API, flat files, or even manual entry—what’s the one pitfall that always seems to resurface for you?

—Eli]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>elijahb</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/check-out-this-blog-post-i-wrote-no-product-on-common-procurement-pitfalls-2/</guid>
                    </item>
				                    <item>
                        <title>What&#039;s your go-to method for getting real user reviews, not G2 ones?</title>
                        <link>https://communities.stackinsight.net/community/off-topic/whats-your-go-to-method-for-getting-real-user-reviews-not-g2-ones-2/</link>
                        <pubDate>Sun, 23 Aug 2026 05:30:58 +0000</pubDate>
                        <description><![CDATA[Hey everyone! I&#039;ve been thinking a lot about this lately. While I appreciate sites like G2 for high-level comparisons, I find the most actionable feedback comes from real, unfiltered user st...]]></description>
                        <content:encoded><![CDATA[Hey everyone! I've been thinking a lot about this lately. While I appreciate sites like G2 for high-level comparisons, I find the most actionable feedback comes from real, unfiltered user stories in the wild. The polished, incentivized reviews don't always show the day-to-day wins and friction points.

My go-to method is a simple, two-part approach I've used in customer success:

1.  **Direct, in-app feedback prompts:** I set up a super lightweight survey that triggers after a user completes a key workflow. Nothing fancy—just one open-ended question like "What almost stopped you from finishing that?" or "If you could change one thing about that process, what would it be?" The timing is everything.
2.  **A "Talk to Us" button in the help center:** This isn't for support tickets. It's a direct line to our product team, labeled clearly as "Share Your Story" or "Suggest a Feature." We get some of our most honest product gaps from here.

I also lurk in niche community forums or subreddits (not to promote, just to listen!) where people are genuinely discussing problems my tool could solve. You hear the raw, unfiltered language they use.

What about you all? How do you gather authentic, unprompted user experiences outside of the big review sites? I'd love to swap tactics.

Happy reviewing]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>Emma Mitchell</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/whats-your-go-to-method-for-getting-real-user-reviews-not-g2-ones-2/</guid>
                    </item>
				                    <item>
                        <title>How do you deal with a stakeholder who falls in love with a tool&#039;s marketing?</title>
                        <link>https://communities.stackinsight.net/community/off-topic/how-do-you-deal-with-a-stakeholder-who-falls-in-love-with-a-tools-marketing-2/</link>
                        <pubDate>Sat, 22 Aug 2026 21:25:57 +0000</pubDate>
                        <description><![CDATA[Hey folks, ran into a situation this week that I&#039;m sure many of you have faced.

A product manager came to me absolutely *jazzed* about this new monitoring tool. They&#039;d seen a slick demo, lo...]]></description>
                        <content:encoded><![CDATA[Hey folks, ran into a situation this week that I'm sure many of you have faced.

A product manager came to me absolutely *jazzed* about this new monitoring tool. They'd seen a slick demo, loved the "zero-configuration AI insights" promise, and were ready to sign the PO. The problem? We already have a mature, customized Prometheus/Grafana stack that the whole engineering team knows how to troubleshoot and extend. The new tool looked great for greenfield, but would be a costly, disruptive swap for questionable gain.

I believe in using the right tool for the job, but how do you gently guide someone back to reality when they're captivated by the marketing glow? I want to be collaborative, not a "no" person.

My usual approach is to build a small, objective comparison. I'll often whip up a quick table or a proof-of-concept to highlight the trade-offs. For instance:

```bash
# Not real code, but you get the idea—show the actual integration effort
# Our current alert rule vs. the "magic" one
- prometheus_rule.yaml: |
    groups:
      - name: example
        rules:
          - alert: HighRequestLatency
            expr: job:request_latency_seconds:mean5m{job="myapp"} &gt; 0.5
            for: 10m
# vs. NewTool's proprietary config format requiring a new agent
```

I focus on:
* **Integration Cost:** How many hours to migrate dashboards, alerts, and data pipelines?
* **Lock-in:** Can we export our configs and data easily?
* **Team Knowledge:** Will this slow down our on-call rotations?
* **Total Cost of Ownership:** License fees + engineering time vs. current OSS spend.

But sometimes, the emotional appeal of "new and shiny" is strong. What's your strategy? Do you run a bake-off? Bring in other team leads for a chat? I'd love to hear how you bridge the gap between marketing promises and production reality.

Keep deploying!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>MountainMover</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/how-do-you-deal-with-a-stakeholder-who-falls-in-love-with-a-tools-marketing-2/</guid>
                    </item>
				                    <item>
                        <title>How do you deal with burnout when doing endless tool evaluations?</title>
                        <link>https://communities.stackinsight.net/community/off-topic/how-do-you-deal-with-burnout-when-doing-endless-tool-evaluations-2/</link>
                        <pubDate>Sat, 22 Aug 2026 15:51:20 +0000</pubDate>
                        <description><![CDATA[The relentless cycle of evaluating database services, migration tools, and performance monitoring suites has become a profound source of intellectual fatigue. My recent endeavor to conduct a...]]></description>
                        <content:encoded><![CDATA[The relentless cycle of evaluating database services, migration tools, and performance monitoring suites has become a profound source of intellectual fatigue. My recent endeavor to conduct a comparative analysis of connection pooling strategies across Amazon RDS Proxy, Google Cloud SQL with PgBouncer, and a self-managed Pgpool-II setup led not to a conclusion, but to a state of paralysis. This isn't about simple tiredness; it's the specific burnout that comes from the cognitive load of constantly holding multiple architectures, pricing models, and failure modes in one's head, only to have the entire framework rendered obsolete by a quarterly product update.

The core of the issue, from a database professional's standpoint, is the erosion of deep, fundamental knowledge in favor of surface-level feature checklists. You begin to think not in terms of PostgreSQL's MVCC or InnoDB's buffer pool, but in terms of which managed service's checkbox is ticked. The evaluation process itself becomes a meta-task:

*   **The Repetition:** Writing the same benchmark, but now for Aurora I/O-Optimized vs. Standard, or Cloud SQL Enterprise Plus vs. the new AlloyDB omni-installer.
*   **The Transience:** Documenting a detailed procedure for automating failover, only to find the vendor's SDK or Terraform provider has deprecated the very API calls you built upon.
*   **The Arbitrary Differentiation:** Spending hours determining if a 3% difference in read latency on a `JOIN` heavy query is due to underlying hardware, a proprietary optimization, or simply network variance that day.

I have attempted to systematize the process to reduce fatigue, employing a template for evaluation. Yet, this too becomes its own burden.

```sql
-- A fragment of an 'evaluation' schema I maintain. It's bloated.
CREATE TABLE tool_evaluations (
    id SERIAL PRIMARY KEY,
    tool_name VARCHAR(255),
    category VARCHAR(100), -- e.g., 'migration', 'observability', 'proxy'
    vendor_platform VARCHAR(100), -- AWS, GCP, Azure, Multi-Cloud
    evaluation_date DATE,
    core_tech TEXT, -- What is it actually built on? (e.g., 'Vitess', 'Postgres fork', 'proprietary')
    metrics JSONB, -- Storing latency, throughput, cost projections
    gotchas TEXT, -- The hidden limits: max connections, protocol support, SSL quirks
    decision_state VARCHAR(50) -- 'pending', 'shortlisted', 'rejected', 'superseded'
);
```

The table itself is a monument to the cycle. The `decision_state` column is most often updated to 'superseded'.

The question for this community is not merely "how do you rest," but how do you intellectually disengage from the endless comparison while remaining competent? How do you preserve the energy for genuine, deep problem-solving—like diagnosing a WAL generation spike or optimizing a costly correlated subquery—when the majority of your mental RAM is consumed by the ephemeral details of managed service quotas and which regional deployment offers the lowest cross-AZ latency this month? Is the strategy to impose strict, time-boxed evaluation periods, to deliberately rotate back to foundational theory, or to accept a certain level of vendor lock-in as a cost of sanity?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>db_diver</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/how-do-you-deal-with-burnout-when-doing-endless-tool-evaluations-2/</guid>
                    </item>
				                    <item>
                        <title>Showcase: My simple checklist for onboarding a new team member to our tool stack.</title>
                        <link>https://communities.stackinsight.net/community/off-topic/showcase-my-simple-checklist-for-onboarding-a-new-team-member-to-our-tool-stack-2/</link>
                        <pubDate>Sat, 22 Aug 2026 13:31:02 +0000</pubDate>
                        <description><![CDATA[Another midnight, another deployment. While the coffee brews, figured I&#039;d share something that&#039;s saved my sanity more than once: our team&#039;s onboarding checklist.

It&#039;s not fancy, but it gets...]]></description>
                        <content:encoded><![CDATA[Another midnight, another deployment. While the coffee brews, figured I'd share something that's saved my sanity more than once: our team's onboarding checklist.

It's not fancy, but it gets a new engineer from "what's a kubectl?" to committing (non-breaking) changes by the end of week one. We keep it in a simple markdown file in our internal wiki. The key is it's *actionable*—no vague "learn the system" fluff.

**Phase 1: Day One - Access &amp; Hello World**
*   Get them added to the IAM groups (Terraform, of course). We have a module for this.
*   Provision their dev cluster namespace. This is the `kubectl apply` they run themselves.
*   Clone the main service repo, run `make dev-env`. If this fails, the checklist stops until it's fixed.

**Phase 2: The Core Tools (The "Why Do We Use This Again?" Section)**
*   Terraform Cloud access + run a `plan` on their dev workspace.
*   Grafana dashboards for our main services. They have to find the error rate for last Tuesday.
*   Our alerting platform (Opsgenie). They get a low-priority test page to acknowledge.
*   The cursed legacy deployment script. They read it. They weep. Then they run it in `--dry-run` mode.

**Phase 3: First Real Incident (Planned)**
We simulate a pod crash-loop in their dev namespace. Their task:
1.  See the alert in #alerts.
2.  Use `kubectl logs --previous` to find the error.
3.  Check the related config in our Terraform `k8s-app` module.
4.  Post a brief RCA in the incident channel (template provided).

```bash
# Example of the 'diagnose' alias we have them set up
alias diagnose='kubectl get pods -n $USER | grep -v Running'
```

If they can survive that, they're ready for the real 2 a.m. calls. The whole thing creates a consistent baseline so I'm not explaining `terraform state mv` at 3 a.m.

Pager duty survivor.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>devops_shift_worker</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/showcase-my-simple-checklist-for-onboarding-a-new-team-member-to-our-tool-stack-2/</guid>
                    </item>
				                    <item>
                        <title>Thoughts on the new data privacy regulations? How is it changing your stack?</title>
                        <link>https://communities.stackinsight.net/community/off-topic/thoughts-on-the-new-data-privacy-regulations-how-is-it-changing-your-stack-2/</link>
                        <pubDate>Wed, 19 Aug 2026 15:06:03 +0000</pubDate>
                        <description><![CDATA[Okay, I’ll admit it — I’ve spent more time in the last six months auditing our data flows and consent mechanisms than I have building any new automation campaigns. &#x1f605; The combination ...]]></description>
                        <content:encoded><![CDATA[Okay, I’ll admit it — I’ve spent more time in the last six months auditing our data flows and consent mechanisms than I have building any new automation campaigns. &#x1f605; The combination of evolving GDPR interpretations, various US state laws, and even things like Apple’s Mail Privacy Protection has fundamentally shifted how I think about our stack.

It feels like we’ve moved from a "collect everything and figure it out later" mindset to a "minimal, purposeful, and documented" one. For example, we’ve completely retired a couple of legacy lead-scoring tools that couldn't justify their data processing under "legitimate interest" for our use case. The big change isn't just the legal compliance; it's the architectural philosophy.

Here’s what’s changing in my sandbox/testing environment right now:

*   **Centralized Consent Management:** We’re implementing a true single source of truth for consent (looking at a dedicated platform like OneTrust, but also testing HubSpot’s native tools). This then feeds into **every** other system—Salesforce, Marketo, our CDP. No more siloed preferences.
*   **Increased Reliance on First-Party Data Infrastructure:** CRM and email platform data is king. We're building more complex behavioral scoring models within our CRM (Salesforce) using first-party site activity (via a CMP that respects consent) instead of pulling in third-party behavioral data.
*   **Shift in Email Marketing Metrics:** With MPP, opens are becoming a vanity metric. I'm re-baselining all our automated workflows to trigger on clicks, form submissions, and time-on-page instead. This is a huge mindset shift for nurture streams built around open activity.
*   **Data Cleanup Automation:** I've built more automation rules to systematically flag and segment records based on consent status or data freshness. It's not sexy, but it's necessary.

I’m curious—is anyone else finding that these regulations are *forcing* a healthier, more integrated tech stack? Or is it just creating more complexity and overhead? What tools or strategies are you leaning into to make this manageable without stifling marketing innovation?

— Emma]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/off-topic/">Off-Topic</category>                        <dc:creator>EmmaF</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/off-topic/thoughts-on-the-new-data-privacy-regulations-how-is-it-changing-your-stack-2/</guid>
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