AWS Big Data

DECEMBER 4, 2024

For instance, Domain A will have the flexibility to create data products that can be published to the divisional catalog, while also maintaining the autonomy to develop data products that are exclusively accessible to teams within the domain. Consumer feedback and demand drives creation and maintenance of the data product.

Metadata 94

Metadata Data Governance Data Quality Data-driven 94

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. This will save the current SQL query book, and the status of the notebook will change from Draft to Saved. Choose Run all.

Visualization 72

Visualization Data Processing Testing Publishing 72

DataKitchen

DECEMBER 20, 2020

They give data scientists tools to instantiate development sandboxes on demand. They automate the data operations pipeline and create platforms used to test and monitor data from ingestion to published charts and graphs.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 115

Management Cost-Benefit Data Transformation Optimization 115

CIO Business Intelligence

APRIL 8, 2025

Build data validation rules directly into ingestion layers so that insufficient data is stopped at the gate and not detected after damage is done. Use lineage tooling to trace data from source to report. Understanding how data transforms and where it breaks is crucial for audibility and root-cause resolution.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

APRIL 26, 2021

GSK’s DataOps journey paralleled their data transformation journey. GSK has been in the process of investing in and building out its data and analytics capabilities and shifting the R&D organization to a software engineering mindset. Organizations should be optimizing and driving their data teams with data.” .

Measurement 246

Measurement Metrics Data-driven Dashboards 246

datapine

SEPTEMBER 29, 2022

This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate. Data time-to-value: evaluates how long it takes you to gain insights from a data set. date, month, and year). million a year.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

AWS Big Data

JANUARY 30, 2025

Pattern 1: Data transformation, load, and unload Several of our data pipelines included significant data transformation steps, which were primarily performed through SQL statements executed by Amazon Redshift. The following Diagram 2 shows this workflow. The following Diagram 4 shows this workflow.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

Jen Stirrup

NOVEMBER 30, 2021

In this session, we will start R right from the beginning, from installing R through to data transformation and integration, through to visualizing data by using R in PowerBI. Then, we will move towards powerful but simple to use datatypes in R such as data frames.

Visualization 92

Visualization Dashboards Data Transformation Publishing 92

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. Managing drafts outside the Catalog keeps a clean distinction between phases of the development cycle, leaving only those flows that are ready for deployment published in the Catalog.

Testing 84

Testing Publishing Metadata Interactive 84

AWS Big Data

JUNE 20, 2023

Kinesis Data Firehose is a fully managed service for delivering near-real-time streaming data to various destinations for storage and performing near-real-time analytics. You can perform analytics on VPC flow logs delivered from your VPC using the Kinesis Data Firehose integration with Datadog as a destination.

Dashboards 92

Dashboards Visualization Metrics Data Transformation 92

Jen Stirrup

SEPTEMBER 30, 2021

For example, data can be filtered so that the investigation can be focused more specifically. There are a number of Data Transformation modules which help with these area. That said, it’s often better to clean the data further upstream so it is done closer to the source rather than at the end of a spoke.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

Cloudera

DECEMBER 21, 2021

This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. . Secondly, instead of being tied to the embedded Airflow within CDE, we wanted any customer using Airflow (even outside of CDE) to tap into the CDP platform, that’s why we published our Cloudera provider package.

Snapshot 118

Snapshot Data-driven Optimization Management 118

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics.

Visualization 111

Visualization Dashboards Data-driven Gap analysis 111

erwin

MARCH 26, 2020

Increased data variety, balancing structured, semi-structured and unstructured data, as well as data originating from a widening array of external sources. Reducing the IT bottleneck that creates barriers to data accessibility. Hybrid on-premises/cloud environments that complicate data integration and preparation.

Data-driven 90

Data-driven Unstructured Data Enterprise Machine Learning 90

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. Developers create draft flows , build them out, and test them with the designer before they are published to the central DataFlow catalog.

Testing 100

Testing Cost-Benefit Interactive Visualization 100

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Now that you have addressed all data quality issues identified on the sample, publish the project as a recipe.

Visualization 90

Visualization Cost-Benefit Data Quality Publishing 90

AWS Big Data

OCTOBER 31, 2023

Data is decompressed and stored in a different S3 bucket (transformed data can be stored in the same S3 bucket where data was ingested, but for simplicity, we’re using two separate S3 buckets). The transformed data is then made accessible to Snowflake for data analysis. Set the protocol to Email.

Data Processing 103

Data Processing Management Publishing Visualization 103

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 117

Data Lake Management Metrics Data Warehouse 117

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. That data then fills several database tables. It’s not just a fear of change.

Testing 130

Testing Data-driven Visualization Dashboards 130

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 118

Management Metadata Analytics Dashboards 118

Sisense

OCTOBER 15, 2020

Note that during this entire process, the user didn’t need to define anything except data transformations: The processing job is automatically orchestrated, and exactly-once data consistency is guaranteed by the engine. Finally, click “Publish” in the upper right hand corner, and you’re ready to create a dashboard!

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

MARCH 13, 2024

Developers can use the support in Amazon Location Service for publishing device position updates to Amazon EventBridge to build a near-real-time data pipeline that stores locations of tracked assets in Amazon Simple Storage Service (Amazon S3). This solution uses distance-based filtering to reduce costs and jitter.

Analytics 110

Analytics IoT Metadata Internet of Things 110

Cloudera

JULY 21, 2022

Cloudera Data Warehouse). Efficient batch data processing. Complex data transformations. Triton Digital, for example, uses Rill to deploy self-serve reporting for hundreds of digital media publishers with little or no training. Apache Hive. Large-scale high throughput analytics. Joins and subqueries . Apache Druid.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

Insight

APRIL 8, 2020

For example, they may give applicants access to an API and ask them to query data that satisfies some criteria, or they may share a large dataset and asking applicants to perform some sort of data transformation. At Insight, we use a hybrid approach where we give applicants a link to a problem statement detailed on a Github.

Data Warehouse 96

Data Warehouse Cost-Benefit Software Optimization 96

AWS Big Data

FEBRUARY 6, 2023

For data pipeline orchestration, the Apache Airflow UI is a user-friendly tool that provides detailed views into your data pipeline. When it comes to pipeline health management, each service that your tasks are interacting with could be storing or publishing logs to different locations, such as an S3 bucket or Amazon CloudWatch logs.

Management 92

Management Interactive Publishing Metadata 92

AWS Big Data

APRIL 12, 2023

The solution uses the TPC-DS dataset and unmodified data schema and table relationships, but derives queries from TPC-DS to support the SparkSQL test cases. It is not comparable to other published TPC-DS benchmark results. About the Authors Melody Yang is a Senior Big Data Solution Architect for Amazon EMR at AWS.

Testing 86

Testing Big Data Metadata Optimization 86

AWS Big Data

SEPTEMBER 13, 2024

At this stage, CFM data scientists can perform analytics and extract value from raw data. Resulting datasets are then published to our data mesh service across our organization to allow our scientists to work on prediction models.

Interactive 87

Interactive Strategy Cost-Benefit Data Governance 87

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 100

Data Warehouse KPI Optimization Cost-Benefit 100

Peter James Thomas

MARCH 9, 2020

In the thirteen years that have passed since the beginning of 2007, I have helped ten organisations to develop commercially-focused Data Strategies [1]. However, in this initial article, I wanted to to focus on one tool that I have used as part of my Data Strategy engagements; a Data Maturity Model.

Measurement 67

Measurement Data Strategy Strategy Modeling 67

Ontotext

MARCH 27, 2024

For example, a node in an LPG with a given label does not guarantee anything about its properties and data type (because it is a string and represents no semantics). LPG lacks schema and semantics, which makes it inappropriate for publishing and sharing of data. This makes LPGs inflexible.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python. Provide the following SQL statement.

Data Analytics 85

Data Analytics Analytics IoT Data Lake 85

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

Ontotext

APRIL 4, 2019

Milena Yankova : What we did for the BBC in the previous Olympics was that we helped journalists publish their reports faster. Milena Yankova : The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. I think artists can relax.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

Alation

MARCH 22, 2022

This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house. They can better understand data transformations, checks, and normalization. They can better grasp the purpose and use for specific data (and improve the pipeline!). Transparency is key.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52