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

Ryan Yackel June 14, 2023 Understanding Data Quality Testing Data quality testing refers to the evaluation and validation of a dataset’s accuracy, consistency, completeness, and reliability. 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

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. Beginning backtest for 1 date(s) and 1 check(s).

Big Data 85

Big Data Metadata Data Warehouse Data 85

Monte Carlo

DECEMBER 19, 2022

Here are the 7 must-have checks to improve data quality and ensure reliability for your most critical assets. Data quality testing is the process of validating that key characteristics of a dataset match what is anticipated prior to its consumption. Essentially, does this data reflect reality?

High Quality Data 52

High Quality Data Data Bytes SQL 52

Monte Carlo

AUGUST 8, 2023

While this process varies from organization to organization, these unit tests are typically applied by the data engineer after they have built the data pipeline architecture. From this perspective, the data validation process looks a lot like any other DataOps process.

Data Validation 52

Data Validation Data Pipeline SQL Data 52

ProjectPro

FEBRUARY 21, 2023

Azure Data Engineer Associate DP-203 Certification Candidates for this exam must possess a thorough understanding of SQL, Python, and Scala, among other data processing languages. Must be familiar with data architecture, data warehousing, parallel processing concepts, etc. Basic understanding of Microsoft Azure.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

AUGUST 9, 2023

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. Volume tests It’s important to identify data volume changes as quickly as possible.

Finance 52

Finance High Quality Data SQL Data 52