I wrote a blog defining Business Intelligence (BI) back in 2021. So what is BI in 2024? It is still not mind-reading, but close enough. However, everyone defines it differently, but we all agree it’s about turning raw data into “Why did sales drop?” and “Should we panic?” answers. In 2024, BI isn’t just dashboards and spreadsheets – it’s AI whispering predictions, cloud warehouses scaling like TikTok trends, and stakeholders demanding insights yesterday. Let’s break down what’s new (and what’s still gloriously chaotic).
What BI Really Is in 2024
A mix of data alchemy and therapy sessions, where you:
- Collect data (from apps, IoT toasters, and that Excel file Karen swore she’d stop using).
- Clean it (because “revenue” is still sometimes
NULL). - Analyze it (with tools that now have more AI than a sci-fi movie).
- Present it (to execs who still ask, “Can you make it pop more?”).
What’s New Since My Last BI Blog
1. The Cloud Ate Everything
- Data Warehouses: Now Snowflake, Databricks, BigQuery, and Redshift rule. They’re faster, cheaper, and scale like Elon’s ambitions.
- Data Lakes: Where you dump TikTok logs, cat memes (unstructured data), and hope AI finds meaning.
- Lakehouses: A lake + warehouse hybrid. Think of it as a data “tiny home” – compact but somehow fits everything.
Pro Tip: Avoid “data swamps” (lakes gone rogue). No one wants to swim in stale data.
2. ELT > ETL (Mostly)
- ETL: Extract, Transform, Load → “Ikea furniture assembly” (tedious but structured).
- ELT: Extract, Load, Transform → “Toss everything into the cloud and pray” (modern, but chaotic).
- Reverse ETL: Send data back to SaaS tools. For when Salesforce needs a hug from your warehouse.
New Tools: dbt, Fivetran, and Airbyte now handle the heavy lifting. No more coding pipelines in a dark basement.
3. AI/ML: The Hype Train
- Predictive Analytics: “Will this product flop?” → Ask the AI crystal ball.
- AutoML: Let machines build models while you nap. Warning: May hallucinate KPIs.
- Generative AI: ChatGPT writes your SQL. Finally, a junior dev who doesn’t complain.
4. Self-Service BI (Still “Self-Serve” in Theory)
- Power BI, Tableau, Looker: Fancier drag-and-drop, but Karen from Accounting still emails you “How do I filter?”
- Embedded Analytics: Dashboards inside apps. For when your CEO wants metrics while ordering lunch on DoorDash.
5. Data Governance: The Party Police
- GDPR, CCPA: Compliance isn’t optional. “Delete my data” = your new nightmare.
- Data Catalogs: Like Google Maps for your data. “Where’s the Q4 sales table?” → Alation or DataHub knows.
BI Layers in 2024
- Data Sources:
- Old: SQL Server, Excel.
- New: TikTok API, IoT fridges, and “Can we scrape Reddit?” requests.
- Storage:
- Warehouse: Clean, structured data (the “adult” section).
- Lake: Raw data (the “mosh pit” section).
- Lakehouse: Where the adults and mosh pit coexist (with a bouncer named Delta Lake).
- Transformation:
- dbt: SQL + Jinja magic. For people who think YAML is a personality trait.
- Data Mesh: Decentralized data (“You build it, you own it”). Chaos, but organized chaos.
- Analysis:
- Dashboards: Now with AI annotations (“Sales dropped because Mercury is in retrograde”).
- Real-Time Analytics: For when “What’s happening NOW?” is a Slack panic.
Why BI Still Feels Like Herding Cats
- Tool Overload: Choosing between Power BI, Looker, and Sigma is like picking a Netflix show – too many options, no time.
- Data Quality: AI can’t fix “Garbage In, Garbage Out”… yet.
- Stakeholders: Still want “one dashboard that does everything” (RIP, sanity).
The Future? BI That Reads Minds
Until then, BI in 2024 is about:
- Speed: Real-time > batch. “Wait, last quarter?” → Unacceptable.
- Democratization: Letting everyone explore data (but hide the “Delete” button).
- AI Co-Pilots: ChatGPT writing your DAX formulas.
TL;DR: BI is still messy, but now with more AI confetti. 🎉
Ready to upgrade from “gut feeling” to “data-driven”? Just avoid Karen’s Excel file.
Your 2024 BI Starter Pack:
- Tools: dbt + Snowflake + Power BI.
- Mantra: “Trust, but verify the data.”
- Survival Tip: Coffee. Lots of coffee.
