AWS Big Data

OCTOBER 23, 2024

It’s a set of HTTP endpoints to perform operations such as invoking Directed Acyclic Graphs (DAGs), checking task statuses, retrieving metadata about workflows, managing connections and variables, and even initiating dataset-related events, without directly accessing the Airflow web interface or command line tools.

Interactive 113

Interactive Testing Data-driven Data Lake 113

AWS Big Data

APRIL 12, 2023

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). About the Authors Melody Yang is a Senior Big Data Solution Architect for Amazon EMR at AWS. As of the Amazon EMR 6.5 with up to 61% lower costs.

Testing 100

Testing Big Data Metadata Optimization 100

AWS Big Data

NOVEMBER 15, 2023

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. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

AWS Big Data

AUGUST 26, 2024

Solution overview The following diagram illustrates the solution architecture: The solution uses AWS Glue as an ETL engine to extract data from the source Amazon RDS database. Built-in data transformations then scrub columns containing PII using pre-defined masking functions. This saves time over manually defining schemas.

Visualization 115

Visualization Metadata Data Transformation Testing 115

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. This ensures that the data is suitable for training purposes.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog. She helps customers architect data analytics solutions at scale on AWS.

Measurement 104

Measurement Dashboards Data Warehouse Analytics 104

AWS Big Data

OCTOBER 18, 2023

To run HiveQL-based data workloads with Spark on Kubernetes mode, engineers must embed their SQL queries into programmatic code such as PySpark, which requires additional effort to manually change code. About the authors Amit Maindola is a Senior Data Architect focused on big data and analytics at Amazon Web Services.

Big Data 104

Big Data Data Processing Interactive Testing 104

AWS Big Data

APRIL 2, 2024

You can see the decompressed data has metadata information such as logGroup , logStream , and subscriptionFilters , and the actual data is included within the message field under logEvents (the following example shows an example of CloudTrail events in the CloudWatch Logs).

Metadata 110

Metadata Marketing Analytics Data Transformation 110

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 121

Analytics IoT Metadata Internet of Things 121

AWS Big Data

JANUARY 17, 2024

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. The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query.

Data Lake 115

Data Lake Snapshot Big Data Data-driven 115

AWS Big Data

MARCH 9, 2023

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Slice and Dice 97

Slice and Dice Dashboards Analytics Interactive 97

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The Data Catalog now contains references to the machine-readable data. Use the Data Catalog and transform the hospital price transparency data.

Visualization 119

Visualization Dashboards Data-driven Gap analysis 119

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 109

Enterprise Data Warehouse Data Lake Optimization 109

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. Track models and drive transparent processes.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

APRIL 19, 2023

We took this a step further by creating a blueprint to create smart recommendations by linking similar data products using graph technology and ML. In this post, we showed how an organization can augment a data catalog with additional metadata by using ML and Neptune with an automated process.

Technology 104

Technology Data-driven Machine Learning Sales 104

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Alation

JANUARY 17, 2023

Extract, load, Transform (ELT) tools. Data ingestion/integration services. Data orchestration tools. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

APRIL 25, 2024

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

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 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

FEBRUARY 6, 2023

The task_id used can be the name of your choice; here we use add_steps : # EMR steps to be executed by EMR cluster SPARK_TEST_STEPS = [{ 'Name': 'Run Spark', 'ActionOnFailure': 'CANCEL_AND_WAIT', 'HadoopJarStep': { 'Jar': 'command-runner.jar', 'Args': ['spark-submit', '/home/hadoop/aggregations.py', 's3://{}/data/transformed/green'.format(S3_BUCKET_NAME),

Management 98

Management Interactive Publishing Metadata 98

AWS Big Data

APRIL 25, 2023

The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.

Sales 94

Sales Visualization Software Metadata 94

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. Data fabric promotes data discoverability.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

IBM Big Data Hub

JULY 17, 2023

foundation models to help users discover, augment, and enrich data with natural language. Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Rocket-Powered Data Science

MARCH 20, 2023

With all the data in and around the enterprise, users would say that they have a lot of information but need more insights to assist them in producing better and more informative content. This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.”

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

AWS Big Data

OCTOBER 30, 2024

Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone. For this use case, create a data source and import the technical metadata of four data assets— customers , order_items , orders , products , reviews , and shipments —from AWS Glue Data Catalog.

Visualization 119

Visualization Data Lake Testing Data Governance 119

AWS Big Data

DECEMBER 4, 2024

Institutional Data & AI Platform architecture The Institutional Division has implemented a self-service data platform to enable the domain teams to build and manage data products autonomously. The following diagram illustrates the building blocks of the Institutional Data & AI Platform.

Metadata 104

Metadata Data Governance Data Quality Data-driven 104

AWS Big Data

JANUARY 27, 2023

With a unified data catalog, you can quickly search datasets and figure out data schema, data format, and location. The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. Refer to Catalogs for more information.

Data Lake 81

Data Lake Metadata Business Analysis Data-driven 81

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 122

Data Lake Management Metrics Data Warehouse 122

AWS Big Data

AUGUST 1, 2023

For GlueDatabaseName , enter a unique name for the Data Catalog database to hold the Jira data table metadata (the default is jiralake ). This mode will scan all data and disable the change data capture (CDC) features of the stack. The DataBrew job performs data transformation and filtering tasks.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 98

AWS Big Data

MARCH 15, 2023

When designing the data processing pipeline for the attribute API, the Infomedia team wanted to use a flexible and open-source solution for processing data workloads with minimal operational overhead. The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption.

Cost-Benefit 88

Cost-Benefit Data Processing Optimization Data-driven 88

Cloudera

NOVEMBER 22, 2021

In addition, more data is becoming available for processing / enrichment of existing and new use cases e.g., recently we have experienced a rapid growth in data collection at the edge and an increase in availability of frameworks for processing that data. As a result, alternative data integration technologies (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data. Comprehensive data security and data governance (i.e.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

DECEMBER 21, 2023

To ingest the data, smava uses a set of popular third-party customer data platforms complemented by custom scripts. After the data lands in Amazon S3, smava uses the AWS Glue Data Catalog and crawlers to automatically catalog the available data, capture the metadata, and provide an interface that allows querying all data assets.

Data Lake 114

Data Lake Data Warehouse Data-driven B2B 114

AWS Big Data

JANUARY 29, 2025

Amazon EMR has long been the leading solution for processing big data in the cloud. Amazon EMR is the industry-leading big data solution for petabyte-scale data processing, interactive analytics, and machine learning using over 20 open source frameworks such as Apache Hadoop , Hive, and Apache Spark.

Big Data 84

Big Data Data Analytics Analytics Interactive 84

AWS Big Data

NOVEMBER 14, 2024

We use the built-in features of Data Firehose, including AWS Lambda for necessary data transformation and Amazon Simple Notification Service (Amazon SNS) for near real-time alerts. AWS Glue – The AWS Glue Data Catalog is your persistent technical metadata store in the AWS Cloud. Data Architect at AWS.

Data Lake 104

Data Lake Metadata Testing Data-driven 104

AWS Big Data

NOVEMBER 6, 2024

To learn more about how to process Firehose records using Lambda, see Transform source data in Amazon Data Firehose. After executing your Lambda function, Firehose looks for routing information and operations in the metadata fields (in the following format) provided by your Lambda function. b64decode(record['data']).decode('utf-8')

Metadata 115

Metadata Data Lake Management Internet of Things 115