IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Capture and document model metadata for report generation.

Risk 78

Risk Modeling Management Metadata 78

datapine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Why Do You Need Data Quality Management? 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

JANUARY 17, 2024

Another popular transaction data lake use case is incremental query. Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. He is deeply passionate about applying ML/DL and big data techniques to solve real-world problems.

Data Lake 98

Data Lake Snapshot Big Data Data-driven 98

AWS Big Data

NOVEMBER 15, 2023

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer.

Dashboards 99

Dashboards Analytics Metadata Data Warehouse 99

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 89

Enterprise Data Warehouse Data Lake Optimization 89

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Let’s refer to this S3 bucket as the raw layer. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9

Data Lake 84

Data Lake Dashboards Metrics Metadata 84