AWS Big Data

JANUARY 15, 2025

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. With a unified catalog, enhanced analytics capabilities, and efficient data transformation processes, were laying the groundwork for future growth.

IoT 100

IoT Machine Learning Metadata Data-driven 100

CIO Business Intelligence

JUNE 29, 2022

But the features in Power BI Premium are now more powerful than the functionality in Azure Analysis Services, so while the service isn’t going away, Microsoft will offer an automated migration tool in the second half of this year for customers who want to move their data models into Power BI instead. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

JANUARY 27, 2023

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. Apache Flink is a widely used data processing engine for scalable streaming ETL, analytics, and event-driven applications. Transformed data can be stored in Amazon S3.

Data Lake 66

Data Lake Metadata Business Analysis Data-driven 66

CIO Business Intelligence

APRIL 8, 2025

Comparison of modern data architectures : Architecture Definition Strengths Weaknesses Best used when Data warehouse Centralized, structured and curated data repository. Inflexible schema, poor for unstructured or real-time data. Data lake Raw storage for all types of structured and unstructured data.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

AWS Big Data

AUGUST 13, 2024

With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. It enables you to visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. Choose the Job details tab.

Data Processing 98

Data Processing Visualization Data Lake Data Processing 98

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. Education and enablement – Conduct learning interventions to upskill teams on understanding and using the data as a product approach.

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 104

Data Warehouse Analytics Data Lake Data Science 104

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow is a fully managed integration service that you can use to securely transfer data from software as a service (SaaS) applications, such as Google BigQuery, Salesforce, SAP, HubSpot, and ServiceNow, to Amazon Web Services (AWS) services such as Amazon Simple Storage Service (Amazon S3) and Amazon Redshift, in just a few clicks.

Analytics 94

Analytics Data Warehouse Big Data Metrics 94

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 106

IoT Data Warehouse Cost-Benefit Reporting 106

AWS Big Data

APRIL 11, 2023

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

Forecasting 83

Forecasting Management IoT Data-driven 83

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 103

Data Lake Data Warehouse Data-driven B2B 103

Cloudera

JUNE 1, 2021

These acquisitions usher in a new era of “ self-service ” by automating complex operations so customers can focus on building great data-driven apps instead of managing infrastructure. Datacoral powers fast and easy data transformations for any type of data via a robust multi-tenant SaaS architecture that runs in AWS.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 118

Data Warehouse Testing Data Quality Reporting 118

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 6, 2023

Transform the YARN job history logs from JSON to CSV After obtaining YARN logs, you run a YARN log organizer, yarn-log-organizer.py, which is a parser to transform JSON-based logs to CSV files. The parser also has other capabilities, including sorting events by time, removing dedicates, and merging multiple logs.

Dashboards 83

Dashboards Optimization Data Lake Cost-Benefit 83

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 76

Reporting Metrics Optimization Data Lake 76

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. The data scientists and IT professionals were amazed, and they couldn’t believe their eyes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

IBM Big Data Hub

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

JUNE 29, 2023

In our solution, we create a notebook to access automotive sensor data, enrich the data, and send the enriched output from the Kinesis Data Analytics Studio notebook to an Amazon Kinesis Data Firehose delivery stream for delivery to an Amazon Simple Storage Service (Amazon S3) data lake.

Data Analytics 84

Data Analytics Analytics IoT Data Lake 84

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

CIO Business Intelligence

AUGUST 7, 2024

The project’s primary objectives were to maintain 100% functionality of the EMR during planned failover events; achieving a recovery point objective of less than one minute; and meet a recovery time objective of two hours for critical services. It also crafted multiple machine learning and AI models to tackle business challenges. “We

IT 119

IT Insurance Cost-Benefit Testing 119

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data. Choose Create Firehose stream.

Metadata 108

Metadata Data Lake Management Internet of Things 108

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76

AWS Big Data

NOVEMBER 14, 2024

Key services in the solution include Amazon API Gateway , Amazon Data Firehose , and Amazon Location Service. The challenge In the event of a disaster e.g. water flood, there is usually a lack of terrestrial data connectivity that prevents monitoring stations from taking actionable measures in real time.

Data Lake 93

Data Lake Metadata Testing Data-driven 93