Monte Carlo

OCTOBER 5, 2023

Ensure data quality Even if there are no errors during the ETL process, you still have to make sure the data meets quality standards. High-quality data is crucial for accurate analysis and informed decision-making. Different perspectives can often shed light on elusive issues.

Data Cleanse 52

Data Cleanse ETL Tools Datasets High Quality Data 52

Databand.ai

JUNE 14, 2023

It enables: Enhanced decision-making: Accurate and reliable data allows businesses to make well-informed decisions, leading to increased revenue and improved operational efficiency. Risk mitigation: Data errors can result in expensive mistakes or even legal issues.

Amazon Web Services 52

Amazon Web Services Datasets High Quality Data ETL Tools 52

Maxime Beauchemin

JANUARY 20, 2017

The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own. Let’s highlight the fact that the abstractions exposed by traditional ETL tools are off-target.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Databand.ai

JULY 5, 2023

A reliable observability tool should provide customizable alerting options based on specific conditions or thresholds. Incorporating these features into your data observability strategy will enable you to maintain high-quality data pipelines and make informed decisions about optimizing performance.

Data Pipeline 52

Data Pipeline Data Lake Data Warehouse Datasets 52

Monte Carlo

DECEMBER 19, 2022

Too much data Too much data might not sound like a problem (it is called big data afterall), but when rows populate out of proportion, it can slow model performance and increase compute costs. Freshness tests can be created manually using SQL rules, or natively within certain ETL tools like the dbt source freshness command.

High Quality Data 52

High Quality Data Data Bytes SQL 52

Towards Data Science

JUNE 16, 2023

Mapping out these use cases requires you to have a deep understanding of how your company works, what’s most important to your stakeholders and what potential implications of issues are. To identify dashboards that are business critical, start by looking at your business use cases.

BI 73

BI Data ETL Tools Machine Learning 73

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale.

Big Data 85

Big Data Metadata Data Warehouse Data 85