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 101

Metadata Data Lake Visualization Data Quality 101

datapine

SEPTEMBER 29, 2022

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. 2 – Data profiling. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

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. Choose Save.

Visualization 71

Visualization Data Processing Testing Publishing 71

Ontotext

NOVEMBER 18, 2021

And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own. You have to take care of data extraction, transformation and loading, and of visualization.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 117

Management Metadata Analytics Dashboards 117

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Wayne Yaddow

MARCH 5, 2025

The goal is to examine five major methods of verifying and validating data transformations in data pipelines with an eye toward high-quality data deployment. First, we look at how unit and integration tests uncover transformation errors at an early stage. Applicability by Transformation Type 2.

Testing 52

Testing Data Transformation Statistics Metadata 52

CIO Business Intelligence

APRIL 30, 2024

Together the technologies aim to help business users and “novice” data analysts explore their data and gain insights without having to resort to data experts. This is really empowering everyone to be a data expert,” Maxon said. “It Shared Dimensions and Composable Data Sources.

Analytics 96

Analytics Metrics Visualization Dashboards 96

Wayne Yaddow

FEBRUARY 18, 2025

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

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. They can use their own toolsets or rely on provided blueprints to ingest the data from source systems.

Dashboards 106

Dashboards Analytics Metadata Data Warehouse 106

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 110

Visualization Dashboards Data-driven Gap analysis 110

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 93

Measurement Dashboards Data Warehouse Analytics 93

Octopai

AUGUST 11, 2024

By reverse-engineering, parsing, and converting scripts, Octopai seamlessly connects all data points within and across organizational systems. While open-source tools such as Apache Atlas, Open Metadata, Egeria, Spline, and OpenLineage offer valuable capabilities, they come with their own sets of pros and cons.

Metadata 40

Metadata Visualization Data Quality Data Governance 40

Cloudera

DECEMBER 9, 2022

Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. A reimagined visual editor to boost developer productivity and enable self service. Enabling self-service for developers.

Testing 100

Testing Cost-Benefit Interactive Visualization 100

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever. About Octopai: Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market.

Metadata 52

Metadata ROI Machine Learning Data Quality 52

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

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 109

Analytics IoT Metadata Internet of Things 109

Cloudera

MARCH 14, 2023

Once a draft has been created or opened, developers use the visual Designer to build their data flow logic and validate it using interactive test sessions. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Testing 84

Testing Publishing Metadata Interactive 84

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 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

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

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 103

Data Lake Data Warehouse Data-driven B2B 103

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Reporting 52

Alation

JANUARY 17, 2023

Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data. You should pick those that allow for easy integration and can create beautiful data visualizations. These help data analysts visualize key insights that can help you make better data-backed decisions.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

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 79

Sales Visualization Software Metadata 79

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.

Data Lake 90

Data Lake Dashboards Metrics Metadata 90

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

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 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

Jet Global

JULY 19, 2023

New Dashboard Layout allows “locking” visual position, swap visual position and adaptive layout for mobile devices. Insiders' Guide to Self-Service Analytics Download Now Visual Enhancements Application and development teams are moving beyond data visualization to data storytelling.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Jet Global

MARCH 14, 2024

Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric. It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance.

Analytics 52

Analytics Management Reporting Data Quality 52

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

AWS Big Data

DECEMBER 2, 2024

AWS Glue establishes a secure connection to HubSpot using OAuth for authorization and TLS for data encryption in transit. AWS Glue also supports the ability to apply complex data transformations, enabling efficient data integration and preparation to meet your needs.

Data Lake 88

Data Lake Testing Data Integration Metadata 88

DataKitchen

JANUARY 23, 2023

To capture a more complete picture of the data’s journey, it is important to have a DataOps Observability system in place. Data lineage is static and often lags by weeks or months. Data lineage is often considered static because it is typically based on snapshots of data and metadata taken at a specific time.

Testing 130

Testing Data Governance Data Quality Data-driven 130