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

ProjectPro

FEBRUARY 8, 2023

ETL developers play a vital role in designing, implementing, and maintaining the processes that help organizations extract valuable business insights from data. The purpose of ETL is to provide a centralized, consistent view of the data used for reporting and analysis.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Meltano

JANUARY 25, 2023

A curated list of the top 9 must read blogs on data. The data world is in turmoil and lots of exciting things happen every day, week and year. At Meltano we’re ourselves avid users of data, data engineers, data PMs, and data enthusiasts through and through. There are many advantages!

Pipeline-centric 52

Pipeline-centric Database-centric Data Warehouse SQL 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. link] NVIDIA: What Is Trustworthy AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

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

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

Data Engineering Weekly

OCTOBER 30, 2022

I found the blog helpful in understanding the generative model’s historical development and the path forward. link] Sponsored- [New eBook] The Ultimate Data Observability Platform Evaluation Guide Considering investing in a data quality solution? The author explains how to dump the history of blockchains into S3.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 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

Picnic Engineering

DECEMBER 12, 2023

This blog post delves into the learnings and challenges on our journey towards implementing and scaling state-of-the-art deep learning approaches. The rich context provided by our Snowflake-powered Data Warehouse enhances their performance, allowing us to create a robust feature set for training.

Machine Learning 52

Machine Learning Deep Learning Food High Quality Data 52

Airbnb Tech

NOVEMBER 24, 2020

During this transformation, Airbnb experienced the typical growth challenges that most companies do, including those that affect the data warehouse. In the first post of this series, we shared an overview of how we evolved our organization and technology standards to address the data quality challenges faced during hyper growth.

Data Warehouse 52

Data Warehouse Certification Data Pipeline Data 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

ProjectPro

FEBRUARY 16, 2023

of data engineer job postings on Indeed? If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. But how does SQL play a vital role here?

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

dbt Developer Hub

APRIL 24, 2023

To that end, we needed to have both the legacy Alteryx workflow output table and the refactored dbt model materialized in the project’s data warehouse. Then we used the macros available in audit_helper to compare query results, data types, column values, row numbers and many more things that are available within the package.

BI 83

BI Data Workflow SQL Data Pipeline 83

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. QuerySurge – Continuously detect data issues in your delivery pipelines.

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

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 67

Raw Data Data Business Intelligence High Quality Data 67

Ascend.io

JUNE 8, 2023

However, transforming data into a product so that it can deliver outsized business value requires more than just a mission statement; it requires a solid foundation of technical capabilities and a truly data-centric culture. It is the stage where data truly becomes a product, delivering tangible value to its end users.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Knowledge Hut

OCTOBER 13, 2023

It improves performance by minimizing data transferred to Power BI for processing. Transform Data in Source: Whenever possible, perform data transformations in the source database or data warehouse before loading the data into Power BI. Use data dictionaries to document your data.

BI 52

BI Business Analyst Datasets Raw Data 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. One of our customers needed the ability to export/import data between systems and create data products from this source data.

IT 52

IT AWS Software Engineer Software Engineering 52

ProjectPro

SEPTEMBER 11, 2021

This blog contains a list of business analyst interview questions and answers. So, if you are considering a career in the management field and aspiring to become a Business Analyst, read this blog to understand what kind of questions are asked in a business analyst interview. Switch to the Ribbon Data tab.

Business Analyst 52

Business Analyst Database-centric MySQL SQL 52

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52