AWS Big Data

DECEMBER 16, 2024

With the ability to browse metadata, you can understand the structure and schema of the data source, identify relevant tables and fields, and discover useful data assets you may not be aware of. You can navigate to the projects Data page to visually verify the existence of the newly created table. option("url", jdbcurl).option("dbtable",

Visualization 95

Visualization Data Processing Testing Publishing 95

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 98

AWS Big Data

JULY 10, 2024

We are excited to announce a new capability of the AWS Glue Studio visual editor that offers a new visual user experience. Now you can author data preparation transformations and edit them with the AWS Glue Studio visual editor. Within the new experience, you can choose from hundreds of prebuilt transformations.

Interactive 115

Interactive Data Integration Visualization Statistics 115

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 110

Metadata Data Lake Visualization Data Quality 110

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

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 114

Data Processing Visualization Data Lake Data Processing 114

AWS Big Data

AUGUST 9, 2024

These processes retrieve data from around 90 different data sources, resulting in updating roughly 2,000 tables in the data warehouse and 3,000 external tables in Parquet format, accessed through Amazon Redshift Spectrum and a data lake on Amazon Simple Storage Service (Amazon S3). We started with 115 dc2.large

Data Lake 110

Data Lake Analytics Data Warehouse Data-driven 110

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. Choose Create job and Visual ETL. Choose Create connection.

Analytics 110

Analytics IT Data Lake Visualization 110

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X With exponentially growing data sources and data lakes, customers want to run more data integration workloads, including their most demanding transforms, aggregations, joins, and queries. 1X (1 DPU) and G.2X You can enable G.4X

Data Lake 110

Data Lake Cost-Benefit Data Integration Data Transformation 110

Cloudera

OCTOBER 13, 2020

CDP Data Hub: a VM/Instance-based service that allows IT and developers to build custom business applications for a diverse set of use cases with secure, self-service access to enterprise data. . 3) Data Visualization is in Tech Preview on AWS and Azure. This is Now. 1) Currently available on AWS only. (2)

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning).

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 115

Data Lake Data Warehouse Data-driven B2B 115

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. Divisions decide how many domains to have within their node; some may have one, others many. Nodes and domains serve business needs and are not technology mandated.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

AWS Big Data

OCTOBER 27, 2023

AWS Glue provides all the capabilities needed for data integration, so you can start analyzing your data and putting it to use in minutes instead of months. AWS Glue provides both visual and code-based interfaces to make data integration easier. Users can more easily find and access data using the AWS Glue Data Catalog.

Analytics 123

Analytics Visualization Data Integration Cost-Benefit 123

AWS Big Data

DECEMBER 5, 2023

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. Figure 1: Workflow illustrating data ingesting, transformation, and visualization using Redshift and CARTO.

Measurement 105

Measurement Dashboards Data Warehouse Analytics 105

AWS Big Data

AUGUST 19, 2024

This allows business analysts and decision-makers to gain valuable insights, visualize key metrics, and explore the data in depth, enabling informed decision-making and strategic planning for pricing and promotional strategies. On the Visual tab, choose Add nodes. Choose Data source – Snowflake in the AWS Glue Studio canvas.

Analytics 118

Analytics Data-driven Data Integration Data Lake 118

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 110

IoT Data Warehouse Cost-Benefit Reporting 110

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. This integration empowers users to go from data to predictions and visualizations faster than ever.

Dashboards 79

Dashboards Data-driven Data Integration Data Lake 79

AWS Big Data

JUNE 29, 2023

Notebooks are provisioned quickly and provide a way for you to instantly view and analyze your streaming data. This pipeline could further be used to send data to Amazon OpenSearch Service or other targets for additional processing and visualization. View the stream data. Transform and enrich the data.

Data Analytics 104

Data Analytics Analytics IoT Data Lake 104

AWS Big Data

FEBRUARY 6, 2023

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget.

Dashboards 98

Dashboards Optimization Data Lake Cost-Benefit 98

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Data engineers are crucial for schema conversion and data transformation, and DBAs can handle cluster configuration and workload monitoring. Platform architects define a well-architected platform.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

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. As a result, alternative data integration technologies (e.g., CRM platforms).

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

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.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 71

Optimization Data Lake Cost-Benefit Reporting 71

AWS Big Data

MARCH 3, 2023

While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source. Customers also required their own repository, an Apache Parquet data lake, which would combine with other data in the customer environment to gather even greater insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 8, 2023

This approach doesn’t solve for data quality issues in source systems, and doesn’t remove the need to have a wholistic data quality strategy. For addressing data quality challenges in Amazon Simple Storage Service (Amazon S3) data lakes and data pipelines, AWS has announced AWS Glue Data Quality (preview).

Data Quality 98

Data Quality Testing Data Warehouse Unstructured Data 98

AWS Big Data

APRIL 5, 2023

In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

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

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

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 mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. However, our initial data architecture led to challenges.

Data Transformation 55

Data Transformation Cost-Benefit Testing Data Lake 55

AWS Big Data

DECEMBER 2, 2024

Using AWS Glue , a serverless data integration service, companies can streamline this process, integrating data from internal and external sources into a centralized AWS data lake. From there, they can perform meaningful analytics, gain valuable insights, and optionally push enriched data back to external SaaS platforms.

Data Lake 104

Data Lake Testing Data Integration Metadata 104