AWS Big Data

OCTOBER 19, 2023

In this post, we discuss different architecture patterns to keep data in sync and up to date between data lakes built on open table formats and data warehouses such as Amazon Redshift. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0 An S3 bucket for storing data.

Data Lake 115

Data Lake Data Warehouse Visualization Snapshot 115

O'Reilly on Data

MARCH 20, 2019

Data poisoning attacks. Data poisoning refers to someone systematically changing your training data to manipulate your model’s predictions. Data poisoning attacks have also been called “causative” attacks.) To poison data, an attacker must have access to some or all of your training data.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

AWS Big Data

JULY 19, 2023

Stage the source data Before we can create and load the dimensions table, we need source data. Therefore, we stage the source data into a staging or temporary table. This is often referred to as the staging layer , which is the raw copy of the source data. There are seven different dimension types.

Modeling 71

Modeling Sales Data Warehouse Snapshot 71

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 81

Management Metadata Testing Internet of Things 81

AWS Big Data

FEBRUARY 1, 2023

Architecturally, we chose a serverless model, and the data lake architecture action line refers to all the architectural gaps and challenging features we determined were part of the improvements. To query data from REST APIs and other data sources, we used PySpark and JDBC modules.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

DataKitchen

MAY 10, 2021

These labor-intensive evaluations of data quality can only be performed periodically, so at best they provide a snapshot of quality at a particular time. DataOps automation that focuses on lowering the rate of errors ensures continuous testing and improvement in data integrity. Location Balance Tests. Historical Balance.

Testing 214

Testing Manufacturing Data Quality Statistics 214

AWS Big Data

MAY 19, 2023

In these scenarios, customers looking for a serverless data integration offering use AWS Glue as a core component for processing and cataloging data. You can now consolidate run logs of AWS Glue jobs on the Airflow console to simplify troubleshooting data pipelines. The steps to upgrade Amazon MWAA to version 2.4.3

Machine Learning 85

Machine Learning Metrics Management Big Data 85

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

AWS Big Data

NOVEMBER 29, 2023

The dbt-glue adapter democratized access for dbt users to data lakes, and enabled many users to effortlessly run their transformation workloads on the cloud with the serverless data integration capability of AWS Glue. Data engineers define dbt models for their data representations. and Viewpoint.

Data Lake 106

Data Lake Management Metrics Data Warehouse 106

Smart Data Collective

AUGUST 21, 2022

But what is the state of AI and Big Data, right now? In this article, we take a snapshot look at the world of information processing as it stands in the present. Big data and AI have what is referred to as a synergistic relationship. The sales department, however, might not know any of it.

Big Data 86

Big Data Cost-Benefit Sales Snapshot 86

DataKitchen

JANUARY 23, 2023

It is important to have additional tools and processes in place to understand the impact of data errors and to minimize their effect on the data pipeline and downstream systems. These operations can include data movement, validation, cleaning, transformation, aggregation, analysis, and more.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

MAY 2, 2022

You also have this year’s approved budget on hand for reference. The source data in this scenario represents a snapshot of the information in your ERP system. During this process, you notice that maintenance and repair expenses were especially high in June and July.

Sales 52

Sales Finance Reporting Software 52