Monte Carlo

AUGUST 31, 2023

Understanding the “rise of data downtime” With a greater focus on monetizing data coupled with the ever present desire to increase data accuracy, we need to better understand some of the factors that can lead to data downtime. We’ll take a closer look at variables that can impact your data next.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 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 67

Raw Data Data Business Intelligence Data Engineering 67

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Monte Carlo

AUGUST 30, 2023

Often, teams run custom data tests as part of a deployment pipeline, or scheduled on production systems via job schedulers like Apache Airflow, dbt Cloud, or via in-built schedulers in your data warehouse solution. Once the models are created and data transformed, `dbt test` should be executed.

SQL 52

SQL Datasets Database High Quality Data 52

Monte Carlo

JUNE 23, 2022

At some point in the last two decades, the size of our data became inextricably linked to our ego. We watched enviously as FAANG companies talked about optimizing hundreds of petabyes in their data lakes or data warehouses. We imagined what it would be like to manage big data quality at that scale.

Big Data 40

Big Data Management Machine Learning Data Warehouse 40