Top Trending LinkedIn Posts about Data Architecture

Data Architecture and Engineering plays a vital role for any Data enthusiast!

Being align with the data sources and crisp clear on your data

Data architecture is dying.

The reason for the decline is multi-factorial, but IMO comes down to three key factors:

1. The rise of

Data architecture always revolves around pushes or pulls!

The "pull" architecture is the most common and includes the following technologies:

A batch computing engine such

Data Architecture: Complex vs. Complicated.

♐️Modern Data Architecture has taken a drastic shift from data warehouse, data lakes and data marts.

🔹It’s beyond that, let’s understand the definition of

Modern Data Architecture has taken a drastic shift from data warehouse, data lakes and data marts.

It’s beyond that, let’s understand the definition of

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Existing data architectures don’t meet the needs of the AI era. With Google Cloud’s data platform, developers can unlock the full potential of

Data architecture is the significant hurdle for AI and ML in Healthcare

#aigovernance #aigovernancezorg #digitalhealth

Why Data Architecture? This is a very good question! Do you want to learn more? Join me on February 22.

Data architecture is not data infrastructure or data platform architecture.

What exactly data architecture is is not entirely clear. Most directly, it's about business

Data architectures have evolved, but the need to continue modernizing remains constant.
Here are some ideas on how to take your data environment to

We are thrilled to be the platform for Cybereason's new SIEM Detection and Response (SDR) solution, built on Observe’s unique and modern architecture.

Here’s

Solid data architecture accelerates AI innovation ensures sustainable growth.

Please check-out the “Digital Revolution with Jim Kunkle” on your favorite podcast provider. After

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

🎉 Data Architecture New Zealand kicks off tomorrow at the Hilton Auckland! Join us for a deep dive into the world of data

Data architectures have evolved over the years, but the need to continue modernizing remains constant.

Understand the next era and how metadata will fuel

Data architecture can hinder your business growth.


Yes, you read that right.

Most business owners fail to realize that the architecture that supports the

Your Data Architecture can delay your retail business growth.


Yes, you read that right.

Most retail business owners need to realize that the architecture that

What is Lake-centric 🌊 Architecture? Why It Matters?

Nikola Ilic and I continue our lakeside chat 😅

At its core, Lake-centric Architecture means

Unlock the potential of your organization with these 5 types of data products.

1. Static Data Products: These are fixed datasets

The rise of data mesh has sparked an important question:

What does "data as a product" (DaaP) really mean? 🤔

DaaP is a mindset

The rise of data mesh has sparked an important question:

What does "data as a product" (DaaP) really mean? 🤔

DaaP is a mindset

Data architecture is so often misunderstood, and is seen as this cost center that keeps working on abstract and inactionable ideas.

But just like

Data Architecture Template

1. Data Stores:  
   Internal databases, data lakes, and external data sources (APIs, cloud storage).

2. Data Acquisition (ETL):  
   Identify data sources, extraction, transformation, and

Data mesh is a anaytical data architecture and operating model where data is treated as a product and owned by teams that most