Data Engineering Weekly

MAY 16, 2023

It involves thorough checks and balances, including data validation, error detection, and possibly manual review. Data Testing vs. These design patterns lead to disjointed data quality tools that add more cost to the pipeline operation than solving the problem. Why I’m making this claim? How to Fix It? Stay Tuned.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Databand.ai

JUNE 20, 2023

Niv Sluzki June 20, 2023 What Is Data Integrity? Data integrity refers to the overall accuracy, consistency, and reliability of data stored in a database, data warehouse, or any other information storage system. 4 Ways to Prevent and Resolve Data Integrity Issues 1.

Data Integration 52

Data Integration Data Validation Pharmaceutical Data Cleanse 52

ProjectPro

FEBRUARY 8, 2023

ETL stands for Extract, Transform, and Load, which involves extracting data from various sources, transforming the data into a format suitable for analysis, and loading the data into a destination system such as a data warehouse. ETL developers play a significant role in performing all these tasks.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Data Engineering Weekly

MARCH 10, 2024

Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal. Pradheep Arjunan - Shared insights on AZ's journey from on-prem to the cloud data warehouses. Thanks to Ideas2IT Technologies for hosting us in their fantastic space.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Striim

JANUARY 4, 2023

Companies need to analyze large volumes of datasets, leading to an increase in data producers and consumers within their IT infrastructures. These companies collect data from production applications and B2B SaaS tools (e.g., This data makes its way into a data repository, like a data warehouse (e.g.,

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Databand.ai

JULY 19, 2023

Despite these challenges, proper data acquisition is essential to ensure the data’s integrity and usefulness. Data Validation In this phase, the data that has been acquired is checked for accuracy and consistency.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Monte Carlo

MAY 26, 2023

This could be the result of a sync issue, the type of information each collects, or how each platform treats different data types. Having the data warehouse as a central source of truth can help present a more consistent view of the campaign. Looker also has a semantic layer called LookML.

Datasets 52

Datasets Data Warehouse Data Validation Data 52

Monte Carlo

MARCH 12, 2024

Google Cloud’s Dataplex is a data fabric tool that enables organizations to discover, manage, monitor, and govern their data across all of their data systems, including their data lakes, data warehouses, data lakehouses, and data marts.

Google Cloud 52

Google Cloud Metadata SQL Data Lake 52

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

dbt Developer Hub

MARCH 23, 2023

Optional: Disable the print_table() command, so the model can be materialized on your data warehouse. With this detailed report, it becomes easier for the AE to find out what could be going wrong with the data refactoring workflow, so the issue can be directly investigated and solved.

Data Warehouse 64

Data Warehouse Generalist SQL Coding 64

Advancing Analytics: Data Engineering

JUNE 10, 2019

After the horror that was the “data silo” days, with clumps of data living in Access databases, Excel spreadsheets and isolated data stores, we’ve had a pretty good run with the classic Kimball data warehouse. However, a data warehouse is a large, sanitary data store.

Data Lake 52

Data Lake Data Warehouse Data Data Validation 52

Data Engineering Weekly

OCTOBER 30, 2022

DuckDB is gaining much attention on this promise, and the Dagster team writes about its experimental data warehouse built on top of DuckDB, Parquet, and Dagster. link] Sponsored: Why You Should Care About Dimensional Data Modeling It's easy to overlook all of the magic that happens inside the data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Monte Carlo

FEBRUARY 15, 2023

But, while this can provide some much-needed context, it doesn’t provide the granularity data teams need to remediate the data problems they uncover—or prevent them from happening again in the future. In the context of data pipelines, column level lineage traces the relationships across and between upstream source systems (i.e.,

Data Validation 52

Data Validation Data Data Engineering Data Engineer 52

Monte Carlo

FEBRUARY 15, 2023

But, while this can provide some much-needed context, it doesn’t provide the granularity data teams need to remediate the data problems they uncover—or prevent them from happening again in the future. In the context of data pipelines, column level lineage traces the relationships across and between upstream source systems (i.e.,

Data Validation 52

Data Validation Data Data Engineering Data Engineer 52

Knowledge Hut

JANUARY 29, 2024

By mastering the art of Data Wrangling, individuals and organizations alike can unlock the true power of data, transforming it from a tangled web of information into a valuable asset that drives innovation, fuels growth, and guides them toward a future were data reigns supreme. What are the six steps of data wrangling?

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Grouparoo

OCTOBER 6, 2021

This provided a nice overview of the breadth of topics that are relevant to data engineering including data warehouses/lakes, pipelines, metadata, security, compliance, quality, and working with other teams. 69 The End of ETL as We Know It Use events from the product to notify data systems of changes.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Grouparoo

DECEMBER 7, 2021

Transmitting data across multiple paths can identify the compromise of one path or a path exhibiting erroneous behavior and corrupting data. Data validation rules can identify gross errors and inconsistencies within the data set. Read more about our Reverse ETL Tools. featured image via unsplash

Data Integration 52

Data Integration Manufacturing ETL Tools Transportation 52

ProjectPro

FEBRUARY 16, 2023

Businesses will be better able to make smart decisions and achieve a competitive advantage if they can successfully integrate data from various sources using SQL. If your database is cloud-based, using SQL to clean data is far more effective than scripting languages. They must load the raw data into a data warehouse for this analysis.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Grouparoo

NOVEMBER 29, 2021

For example, multiple diverse data sources may provide the data used by the processing function for complex processing. The data sourcing may be live data, a copy of the data, or even a pointer to data stored in a different location. It may be raw data, validated data, or big data.

Raw Data 40

Raw Data Big Data Relational Database Data Warehouse 40

Knowledge Hut

SEPTEMBER 25, 2023

They are in charge of designing data storage systems that scale, perform, and are economical enough to satisfy the organization's requirements. They guarantee that the data is efficiently cleaned, converted, and loaded. Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Knowledge Hut

OCTOBER 30, 2023

Data Analysis: Perform basic data analysis and calculations using DAX functions under the guidance of senior team members. Data Integration: Assist in integrating data from multiple sources into Power BI, ensuring data consistency and accuracy. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Christophe Blefari

MARCH 15, 2024

Understand how BigQuery inserts, deletes and updates — Once again Vu took time to deep dive into BigQuery internal, this time to explain how data management is done. Pandera, a data validation library for dataframes, now supports Polars.

Metadata 272

Metadata Datasets Data Data Warehouse 272

dbt Developer Hub

APRIL 30, 2023

Armed with them, I finally saw the magic of the modern data stack and what problems it could solve.

Data Engineering 64

Data Engineering Data Engineer Engineering Finance 64

Databand.ai

AUGUST 30, 2023

Poor data quality can lead to incorrect or misleading insights, which can have significant consequences for an organization. DataOps tools help ensure data quality by providing features like data profiling, data validation, and data cleansing.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Databand.ai

JULY 19, 2023

A Beginner’s Guide [SQ] Niv Sluzki July 19, 2023 ELT is a data processing method that involves extracting data from its source, loading it into a database or data warehouse, and then later transforming it into a format that suits business needs. The data is loaded as-is, without any transformation.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Airbnb Tech

NOVEMBER 28, 2023

However, for all of our uncertified data, which remained the majority of our offline data, we lacked visibility into its quality and didn’t have clear mechanisms for up-leveling it. How could we scale the hard-fought wins and best practices of Midas across our entire data warehouse?

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Edureka

AUGUST 2, 2023

Data integration and transformation: Before analysis, data must frequently be translated into a standard format. Data processing analysts harmonise many data sources for integration into a single data repository by converting the data into a standardised structure.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Data Engineering Podcast

JUNE 16, 2019

This conversation was useful for getting a better idea of the challenges that exist in large scale data analytics, and the current state of the tradeoffs between data lakes and data warehouses in the cloud. What are some of the common antipatterns in data lake implementations and how does Delta Lake address them?

Data Lake 100

Data Lake Lambda Architecture Data Warehouse Hadoop 100

Knowledge Hut

APRIL 19, 2023

It is the process of extracting data from various sources, transforming it into a format suitable for analysis, and loading it into a target database or data warehouse. ETL is used to integrate data from different sources and formats into a single target for analysis. What is an ETL Pipeline?

Data Warehouse 52

Data Warehouse Business Intelligence ETL Tools Data Pipeline 52

Rockset

MARCH 1, 2023

If such query workloads create additional data lags then it will actively cause more harm by increasing your blind spot at the exact wrong time, the time when fraud is being perpetrated. OLTP databases aren’t built to ingest massive volumes of data streams and perform stream processing on incoming datasets.

Data Ingestion 144

Data Ingestion Database Architecture Cloud Storage 144

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

Data Integration 52

Data Integration Process Data Validation Data Governance 52

U-Next

MARCH 7, 2023

In software engineering, data modeling involves applying formal techniques to create a data model for an information system. Dimensional modeling refers to the use of fact and dimension tables to keep a record of historical data in data warehouses. How does a Data Analysis project work?

Data Mining 96

Data Mining Scala Government Data Governance 96

Monte Carlo

MARCH 24, 2023

Database differences and schema management Each database, even in the cloud, stores values a little differently–but those little changes can be big data migration risks. For example, one data leader gave us the example of how two data warehouse store dollar amounts differently.

Data Warehouse 52

Data Warehouse AWS Cloud Data Governance 52

Meltano

JANUARY 25, 2023

Completely Versioned Data Stacks Modern Data Stacks in a Box with DuckDB by Jacob Matson “Why build a bundled Modern Data Stack on a single machine, rather than on multiple machines and on a data warehouse? There are many advantages!

Pipeline-centric 52

Pipeline-centric Database-centric Data Warehouse SQL 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 70

Raw Data Data Business Intelligence High Quality Data 70

Monte Carlo

OCTOBER 1, 2020

In this article we introduce “Key Assets”, a new approach taken by the best data teams to surface your most important data assets for quick and reliable insights. Have you been 3/4ths of the way done with a data warehouse migration only to discover that you don’t know which data assets are right and which ones are wrong?

Data Warehouse 40

Data Warehouse Datasets Data Validation Machine Learning 40

Picnic Engineering

DECEMBER 12, 2023

The rich context provided by our Snowflake-powered Data Warehouse enhances their performance, allowing us to create a robust feature set for training. These models thrive on handling a plethora of input features — from product details and holiday periods to weather predictions, promotional activities, and our unique recipes.

Machine Learning 52

Machine Learning Deep Learning Food High Quality Data 52