AWS Big Data

JUNE 8, 2023

For instructions, refer to Creating and managing Amazon OpenSearch Service domains. For Host , enter events.PagerDuty.com. For more information about anomaly detection and alerts in OpenSearch Service, refer to Anomaly Detection in Amazon OpenSearch and Configuring Alerts in Amazon OpenSearch. For Method , choose POST.

Data Lake 75

Data Lake Dashboards Metrics Testing 75

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 98

Statistics Data Lake Optimization Data-driven 98

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. Slate refers to a family of encoder-only (RoBERTa-based) models, which while not generative, are fast and effective for many enterprise NLP tasks. All watsonx.ai

Enterprise 136

Enterprise Technology Modeling Cost-Benefit 136

AWS Big Data

DECEMBER 13, 2023

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. This solution uses Amazon Aurora MySQL hosting the example database salesdb.

Data Warehouse 94

Data Warehouse Snapshot Data Processing Management 94

AWS Big Data

FEBRUARY 16, 2023

For more details, refer to Amazon QuickSight resource type reference. In this post, we show how to automate the deployment of a QuickSight analysis connecting to an Amazon Redshift data warehouse with a CloudFormation template. For instructions, refer to Authorizing connections from Amazon QuickSight to Amazon Redshift clusters.

Data Warehouse 76

Data Warehouse Sales Visualization Data Processing 76

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 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Data Virtualization

SEPTEMBER 23, 2020

I’m referring not only to our technology partners, but also to our cloud partners that host the Denodo Platform, Denodo is a very partner-friendly company, and here I’d like to share some thoughts about how Denodo works with our partners.

Strategy 52

Strategy Data Processing Technology Digital Transformation 52

AWS Big Data

JUNE 6, 2023

For instructions, refer to Installing or updating the latest version of the AWS CLI. For instructions, refer to Configuration and credential file settings. Also, note that we are using data-team-a as a namespace and emr-job-execution-sa as a service account, which we created in the previous step.

Optimization 67

Optimization Data Lake Cost-Benefit Management 67

AWS Big Data

MARCH 6, 2024

The account on the right hosts the pseudonymization service, which you can deploy using the instructions provided in the Part 1 of this series. For an overview of how to build an ACID compliant data lake using Iceberg, refer to Build a high-performance, ACID compliant, evolving data lake using Apache Iceberg on Amazon EMR.

Metrics 90

Metrics Statistics Testing Data Lake 90

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 59

Metadata Data Lake Data Processing Data-driven 59

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 76

Data Lake Data Analytics Analytics Data Processing 76

AWS Big Data

OCTOBER 17, 2023

Tens of thousands of customers use Amazon Redshift to gain business insights from their data. With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. For more information, refer to Configuring ongoing data replication.

Data Warehouse 82

Data Warehouse Data Processing Data Lake Management 82

Domino Data Lab

APRIL 3, 2019

“Flashpoint” (2018) – GDPR went into effect, plus major data blunders happened seemingly everywhere. Fun fact : I co-founded an e-commerce company (realistically, a mail-order catalog hosted online) in December 1992 using one of those internetworking applications called Gopher , which was vaguely popular at the time. Upcoming Events.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

APRIL 26, 2024

Set up EMR Studio In this step, we demonstrate the actions needed from the data lake administrator to set up EMR Studio enabled for trusted identity propagation and with IAM Identity Center integration. If Lake Formation is not already enabled, refer to Getting started with Lake Formation.

Analytics 85

Analytics Data Lake Management Enterprise 85

AWS Big Data

MARCH 27, 2023

Data lakes have come a long way, and there’s been tremendous innovation in this space. Today’s modern data lakes are cloud native, work with multiple data types, and make this data easily available to diverse stakeholders across the business. In the navigation pane, under Data catalog , choose Settings.

Data Lake 81

Data Lake Data-driven Management Data Architecture 81

AWS Big Data

OCTOBER 23, 2023

Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.

Data Lake 98

Data Lake Visualization Optimization Interactive 98

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. For more information, refer to IAM Policies for invoking AWS Glue job from Step Functions.

Metadata 117

Metadata Visualization Data Lake Data-driven 117

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. with Apache Spark version 3.3.0)

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

AWS Big Data

MARCH 20, 2023

Top line revenue refers to the total value of sales of an organization’s services or products. The data from the S3 data lake is used for batch processing and analytics through Amazon EMR and Amazon Redshift. Operational dashboards are hosted on Grafana integrated with Druid.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

Cloudera

OCTOBER 25, 2022

The data lakehouse is gaining in popularity because it enables a single platform for all your enterprise data with the flexibility to run any analytic and machine learning (ML) use case. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The job runs in the target account. mode('overwrite').save(output_path

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

AUGUST 28, 2023

OpenSearch Ingestion provides a serverless ingestion framework to easily ingest Security Lake data into OpenSearch Service with just a few clicks. For instructions, refer to Creating and managing Amazon OpenSearch Service domains. For instructions, refer to Managing multiple accounts with AWS Organizations. Choose Next.

Dashboards 52

Dashboards Visualization Metadata Management 52

AWS Big Data

JANUARY 22, 2024

Data as a product Treating data as a product entails three key components: the data itself, the metadata, and the associated code and infrastructure. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

AWS Big Data

JUNE 13, 2023

For instructions on installing Keycloak, refer to Keycloak Downloads. Insert your specific host domain name where the Keycloak application resides in the following URL: [link] /realms/aws-realm/protocol/saml/descriptor. Vamsi Bhadriraju is a Data Architect at AWS. Sign in to your Keycloak admin dashboard.

Metadata 52

Metadata Dashboards Business Intelligence Management 52

AWS Big Data

MARCH 26, 2024

It is prudent to consolidate this data into a single customer view, serving as a primary reference for downstream applications, ranging from ecommerce platforms to CRM systems. This consolidated view acts as a liaison between the data platform and customer-centric applications.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

AWS Big Data

FEBRUARY 2, 2023

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. This could be your data lake or application S3 bucket.

Reporting 83

Reporting Data Lake Management Optimization 83

AWS Big Data

SEPTEMBER 22, 2023

At Stitch Fix, we have been powered by data science since its foundation and rely on many modern data lake and data processing technologies. In our infrastructure, Apache Kafka has emerged as a powerful tool for managing event streams and facilitating real-time data processing.

Management 99

Management Metrics Cost-Benefit Data Lake 99

Cloudera

JUNE 6, 2019

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. Over time, workloads start processing more data, tenants start onboarding more workloads, and administrators (admins) start onboarding more tenants. Cloudera Manager (CM) 6.2

Metadata 85

Metadata Data Lake Optimization Strategy 85

AWS Big Data

APRIL 28, 2023

This enables users to mix and match between data domains—as well as utilizing private and public data paths that aren’t necessarily tied to any data domain. For more examples of how ABAC can be used with permission policies, refer to How to scale your authorization needs by using attribute-based access control with S3.

Data Governance 65

Data Governance Management Data-driven Data Lake 65

AWS Big Data

JANUARY 27, 2023

For example, the Flink FileSystem connector has FileSystemTableFactory to read/write data in Hadoop Distributed File System (HDFS) or Amazon Simple Storage Service (Amazon S3), the Flink HBase connector has HBase2DynamicTableFactory to read/write data in HBase, and the Flink Kafka connector has KafkaDynamicTableFactory to read/write data in Kafka.

Data Lake 60

Data Lake Metadata Business Analysis Data-driven 60

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 121

Metadata Cost-Benefit Enterprise Interactive 121

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. Those incremental costs derive from a variety of reasons: Increased data processing costs associated with legacy deployment types (e.g., CRM platforms).

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

Andrew White

JANUARY 11, 2021

On January 4th I had the pleasure of hosting a webinar. It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. It is meant to be a desk-reference for that role for 2021. Data lakes don’t offer this nor should they.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

FEBRUARY 23, 2024

ETL is beneficial for larger data volumes and diverse sources, and may be necessary for data architects, developers, and administrators considering factors like volume, source diversity, accuracy, and efficiency. Data Migration Data migration refers to the process of transferring data from one location or format to another.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52