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Product and Technology

How-to guides, platform updates, and technical insights on data integration, Microsoft Fabric, semantic layers, and building AI-ready data infrastructure with Timextender. 

AI Data Integration

11 min read

AI-Powered Data Automation with Timextender

Processing vast amounts of data with speed and precision is becoming increasingly important for all organizations, regardless of size or industry....

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15 min read

The Ultimate Guide to Data Transformation

Data transformation plays a crucial role in data management. This process reshapes data into formats that are more conducive to analysis, unlocking...

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13 min read

The Ultimate Guide to Semantic Layers

Semantic layers are experiencing a significant resurgence, becoming increasingly vital in the realm of data management. This renewed interest isn't...

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7 min read

Building Scalable Data Architectures: Principles and Best Practices

In the current era of information explosion, businesses and organizations grapple with an unprecedented influx of data, attempting to tame the...

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22 min read

The Ultimate Guide to Data Architecture

As organizations seek to harness the transformative power of data, the need to build a robust foundation that can withstand the test of time becomes...

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18 min read

The Ultimate Guide to Data Automation

As organizations of all sizes strive to harness the power of data analytics, a pressing challenge emerges: the laborious and time-consuming nature of...

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Timextender Unified Metadata Framework

14 min read

Timextender's Unified Metadata Framework Enables Seamless Data Integration

Scroll to the bottom for a summary. Metadata is often referred to as "data about data." Metadata is information that provides context and meaning to...

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5 min read

The Pros and Cons of Analytics as Code

"Analytics as Code" is an approach that applies software development principles to analytics. It treats analytics processes, such as building...

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3 min read

Data Engineers vs Data Scientists – What’s the Difference?

So, you’re a data engineer. Or you’re a data scientist. Or you might consider yourself to be both, but you have one title at work, and there’s always...

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data lake vs data warehouse Timextender

4 min read

Data Lake vs Data Warehouse: What's the Difference?

While data lakes and data warehouses are both important data management tools, they serve very different purposes. If you're trying to determine...

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5 min read

Data Warehouse vs Database: Everything You Need to Know

The data warehouse vs database debate has been going on for many years. Which is better? What are the benefits of each? Is there a correct answer to...

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7 min read

Self-Service Troubleshooting in Timextender

Best practices to solve technical support issues in less time!

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3 min read

Data Warehouse, Data Lake, Data Hub or a Data Platform?

Data warehouse, data lake, data hub, and data platform get used as if they meant the same thing, and vendors add to the confusion by using whichever...

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Data_1

2 min read

Reversing the 80-20 Rule in Data Wrangling for AI and Machine Learning

An average day in the life of a data scientist consists of preparing (identifying, collecting, cleaning, aggregating etc.) data, modeling prepared...

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