Top Trending LinkedIn Posts about data

Data is the new currency in insurance—are you cashing in?

Claims teams that embrace a data-driven mindset will redefine efficiency. Business Intelligence dashboards are

Data courses prepare you for:
"Here's the data, find insights"

Real work prepares you for:
"The data might be wrong, definitions keep changing, different teams have

Data and AI Don’t Speak for Themselves – But People Do! 🔍

Week 45 is heading your way, and a phenomenal way to close

Data Architecture Landscape

In today's data-driven world, choosing the right data architecture pattern is crucial for organizations to harness the full potential of

Data Center Lead Generation 201 (Getting to Decision Makers and Larger Sales)

Have changes in buyer preferences become even more pronounced when trying to

Data is the new gold, but without skilled miners, it remains untapped.

Data engineers are the unsung heroes of the AI revolution.

Their work lays

#Data #Engineering update for #Microsoft #Fabric
You can now use #Notebook switcher to switch between Develop mode, run only, edit or view

🔴 Mastering Kafka for Job Interviews: Your Gateway to High-Demand Data Engineering Roles!
Confluent Kafka, the enterprise version of Apache Kafka, is crucial for

Data and AI Don’t Speak for Themselves – But Data People Like You Do! 🔍

Week 45 is heading your way, and a phenomenal

Data and AI Don’t Speak for Themselves – But Data People Like You Do! 🔍

Week 45 is heading your way, and a phenomenal

Data doesn’t drive decisions.

Here are 5 tips to turn data into actionable insights for users:

1. Focus on the why, not just the what.
2.

Python Machine Learning Projects

↳ The document provides insights on loading datasets with Scikit-learn, highlighting essential keys like target labels, actual labels, feature names,

Data Analysts as a service desk?

Time for a mindset shift!

In many organizations, data teams are still treated like a service desk.

Business teams

Data Scientist in the past:

⏩ Focused primarily on building and deploying models
⏩ Success measured mainly by deployment metrics.

Data Scientist now:

⏩ Continuously monitors and

Data Engineering, Laying The Foundation

Part 6: Data Processing and Analytics

Processing data effectively is at the heart of any impactful data strategy. In data-driven

Data-Driven Decision Making: Are You Leveraging Big Data in Your Estate Agency?

The use of big data in real estate allows agents to predict

Data Mesh: A Simple Explanation
(even your 70-year-old mother will get it!)

Ever wondered how big companies manage their vast amounts of data?

They use

Data and AI Don’t Speak for Themselves – But People Do! 🔍

Week 45 is heading your way, and a phenomenal way to close

Data cleaning can take up around 60-70% of a data professional's time, but mastering it is crucial for effective analysis.

I’ve created a comprehensive

Data privacy regulations are changing the game.

Staying compliant while maintaining ad performance is tough.

☑ Restricted Data Processing (RDP)
↳ Google limits data when users

Data and AI Don’t Speak for Themselves – But People Do! 🔍

Week 45 is heading your way, and a phenomenal way to close

Data viz rule #1: Know your audience

Scientists might want every decimal point.
Executives might just want the big picture.

The science:
Get the numbers right

The

Python Machine Learning Projects

↳ The document provides insights on loading datasets with Scikit-learn, highlighting essential keys like target labels, actual labels, feature names,

𝗗𝗮𝘁𝗮 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 & 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 𝗨𝗞 𝗢𝗿𝗴𝗮𝗻𝗶𝘀𝗮𝘁𝗶𝗼𝗻𝘀

😓 Data leaders often struggle with data silos, outdated systems and regulatory hurdles. But these frustrations should

Data Privacy in 2025: How Analysts Are Adapting to Stricter Regulations

Data Privacy in 2025: Rising Standards, New Challenges 🔐🛠️

Data privacy is taking center

Data Engineering, Laying The Foundation

Part 7: Data Security and Governance

Establishing robust data security and governance is vital for organizations committed to ethical and

Data augmentation is emerging as a highly promising use case for GenAI in data collection—especially when combined with tools like FME and Survey123.

I went from Business Analyst to Data Scientist, without a bootcamp or a Master’s degree.

Here's how I did it:

𝟭/ 𝗙𝗼𝘂𝗻𝗱 𝘄𝗮𝘆𝘀 𝘁𝗼 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲

Data privacy is the top priority:

And the truth?

It's what the audience cares about most.

Ensuring their data remains private and secure.

Data Privacy First:
↳ Your

Data Analytics ≠ Marketing Analytics

Let me say that one more time:

Data Analytics ≠ Marketing Analytics

Many people treat these terms as interchangeable, but that’s