Rockset

FEBRUARY 24, 2023

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Strong schema support : Avro has a well-defined schema that allows for type safety and strong data validation.

Kafka 52

Kafka AWS Amazon Web Services Programming Language 52

Airbnb Tech

NOVEMBER 24, 2020

For a data quality guarantee to be relevant for many of the most important data use cases, we needed to guarantee quality for both data tables and the individual metrics derived from them. When you analyze a metric across any of Airbnb’s suite of data tools, you can be sure you are looking at the same numbers as everybody else.

Data Warehouse 52

Data Warehouse Certification Data Pipeline Data 52

Edureka

AUGUST 29, 2024

Design and maintain pipelines: Bring to life the robust architectures of pipelines with efficient data processing and testing. Collaborate with Management: Management shall collaborate, understanding the objectives while aligning data strategies.

Data Engineering 40

Data Engineering Data Engineer Engineering Generalist 40

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.

Data Lake 52

Data Lake Data Warehouse ETL Tools Data Pipeline 52

Monte Carlo

OCTOBER 1, 2020

As data teams increasingly make the shift from on-prem data warehouses to Snowflake, Redshift, and other cloud warehouses or between cloud warehouses, the ability to know which data is valuable and which data can go the way of the Dodos becomes evermore important.

Data Warehouse 40

Data Warehouse Datasets Machine Learning Data Validation 40

Knowledge Hut

APRIL 20, 2023

Data Governance Examples Here are some examples of data governance in practice: Data quality control: Data governance involves implementing processes for ensuring that data is accurate, complete, and consistent. This may involve data validation, data cleansing, and data enrichment activities.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

ProjectPro

FEBRUARY 16, 2023

Data validations or data type checks can be performed using SQL, while duplicates, foreign key constraints, and NULL checks can all be identified using ETL solutions. Data processing tasks containing SQL-based data transformations can be conducted utilizing Hadoop or Spark executors by ETL solutions.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

JANUARY 31, 2023

Step 4: Data Transformation and Enrichment Data transformation involves changing the format or value inputs to achieve a specific result or to make the data more understandable to a larger audience. Enriching data entails connecting it to other related data to produce deeper insights.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Cloudyard

MARCH 13, 2025

Read Time: 2 Minute, 12 Second In modern data architectures, businesses rely on automated pipelines to ingest, transform, and analyze data efficiently. Loads data with MATCH_BY_COLUMN_NAME = CASE_INSENSITIVE. Logs Processed Files : The processed file names are stored in an array and returned as output.

AWS 52

AWS Data Ingestion Data Validation Data Architecture 52

DataKitchen

JANUARY 23, 2023

Verification is checking that data is accurate, complete, and consistent with its specifications or documentation. This includes checking for errors, inconsistencies, or missing values and can be done through various methods such as data profiling, data validation, and data quality assessments. Did it fail?

Data Governance 52

Data Governance Government Data Pipeline Data 52