Monte Carlo

NOVEMBER 20, 2023

A data migration is the process where old datasets, perhaps resting in outdated systems, are transferred to newer, more efficient ones. Sure, you’re moving data from point A to point B, but the reality is far more nuanced. You have to ensure that data remains intact and consistent during the migration process.

MongoDB 52

MongoDB ETL Tools Database Data 52

Databand.ai

AUGUST 30, 2023

In a DataOps architecture, it’s crucial to have an efficient and scalable data ingestion process that can handle data from diverse sources and formats. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Grouparoo

OCTOBER 6, 2021

Tianhui Michael Li The Three Rs of Data Engineering by Tobias Macey Data testing and quality Automate Your Pipeline Tests by Tom White Data Quality for Data Engineers by Katharine Jarmul Data Validation Is More Than Summary Statistics by Emily Riederer The Six Words That Will Destroy Your Career by Bartosz Mikulski Your Data Tests Failed!

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

SEPTEMBER 25, 2023

Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage. Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations. Improve the scalability, efficiency, and cost-effectiveness of data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Cloudera

AUGUST 31, 2021

These schemas will be created based on its definitions in existing legacy data warehouses. Smart DwH Mover helps in accelerating data warehouse migration. Smart Data Validator helps in extensive data reconciliation and testing. Smart Query Convertor converts queries and views to be made compatible on CDW.

Data Warehouse 81

Data Warehouse Database-centric Metadata Cloud 81

ProjectPro

FEBRUARY 16, 2023

In fact, approximately 70% of professional developers who work with data (e.g., data engineer, data scientist , data analyst, etc.) According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. use SQL, compared to 61.7%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

APRIL 19, 2021

Monitor the quality of data Identify, evaluate and make use of novel tools for data validation and cleansing. Define novel data collection strategies as per business needs. Develop reports, data dashboards, and visualizations based on the analysis. Develop database querying language skills in SQL and NoSQL.

Portfolio 40

Portfolio Data Finance Certification 40