AWS Big Data

AUGUST 9, 2024

We carried out the migration as follows: We created a new cluster with eight ra3.4xlarge nodes from the snapshot of our four-node dc2.8xlarge cluster. TB of data. It represents a significant decrease in the delivery time of our critical data analytics processes. We removed the DC2 cluster and completed the migration.

Data Lake 107

Data Lake Analytics Data Warehouse Data-driven 107

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca build a data lake? Why did Orca choose Apache Iceberg?

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

Cloudera

AUGUST 3, 2022

Customers will now get the same consistent view of their data with the analytic processing engine of their choice without any compromises. . Within CDP, Shared Data Experience (SDX) provides centralized governance, security, cataloging, and lineage. Fine grained access control (FGAC) with Spark. Introducing Spark Secure Access Mode.

Snapshot 90

Snapshot Cost-Benefit Machine Learning Data Science 90

AWS Big Data

JULY 26, 2023

To grow the power of data at scale for the long term, it’s highly recommended to design an end-to-end development lifecycle for your data integration pipelines. The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop?

Data Integration 80

Data Integration Snapshot Testing Visualization 80

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 117

Data Lake Management Metrics Data Warehouse 117

AWS Big Data

OCTOBER 11, 2023

The lift and shift migration approach is limited in its ability to transform businesses because it relies on outdated, legacy technologies and architectures that limit flexibility and slow down productivity. It shows a call center streaming data source that sends the latest call center feed in every 15 seconds.

Management 118

Management Metadata Analytics Dashboards 118

AWS Big Data

JANUARY 17, 2024

The Amazon EMR record server component supports table-, column-, row-, cell-, and nested attribute-level data filtering functionality. Deploy the solution via AWS CloudFormation We provide an AWS CloudFormation template that automatically sets up the following services and components: An S3 bucket for the data lake. Choose Create.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Identify all upstream and downstream applications, as well as business processes that rely on the data warehouse. Data transformation experts to convert database stored functions in the producer or consumer.

Data Warehouse 100

Data Warehouse KPI Optimization Cost-Benefit 100

AWS Big Data

MARCH 16, 2023

This post is co-written by Anish Moorjani, Data Engineer at SafetyCulture. Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

AWS Big Data

MARCH 3, 2023

Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights. Each of these tools has its own reporting capabilities that make it difficult to combine the data for integrated and actionable business insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 91

Data Lake Dashboards Metrics Metadata 91

AWS Big Data

JANUARY 27, 2023

To build a data-driven business, it is important to democratize enterprise data assets in a data catalog. With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. The Amazon EMR Flink CDC connector reads the binlog data and processes the data.

Data Lake 67

Data Lake Metadata Business Analysis Data-driven 67

Jet Global

NOVEMBER 7, 2023

Add in the de facto requirement to combine all your reporting data and it presents quite a challenge. As more companies move their data into the cloud, methods for storing and managing that data also adapt and grow. This growth is caused, in part, by the increasing use of cloud platforms for data storage and processing.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

AWS Big Data

FEBRUARY 18, 2025

These include managing complex extract, transform, and load (ETL) processes, handling schema validation, providing reliable delivery, and maintaining custom code for data transformations. Firehose delivers streaming data with configurable buffering options that can be optimized for near-zero latency.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76

AWS Big Data

NOVEMBER 6, 2024

As businesses generate more data from a variety of sources, they need systems to effectively manage that data and use it for business outcomes—such as providing better customer experiences or reducing costs. Second, it allows customers to read and write data concurrently using different frameworks.

Metadata 109

Metadata Data Lake Management Internet of Things 109

DataKitchen

JANUARY 23, 2023

What is data lineage? Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. It is used to understand the provenance of data and how it is transformed and to identify potential errors or issues. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130