AWS Big Data

SEPTEMBER 5, 2024

With auto-copy, automation enhances the COPY command by adding jobs for automatic ingestion of data. 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

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

AUGUST 13, 2024

You will load the event data from the SFTP site, join it to the venue data stored on Amazon S3, apply transformations, and store the data in Amazon S3. The event and venue files are from the TICKIT dataset. For Node parents , select Rename Venue data and Rename Event data.

Data Processing 106

Data Processing Visualization Data Lake Data Processing 106

AWS Big Data

MARCH 13, 2024

Using EventBridge integration, filtered positional updates are published to an EventBridge event bus. Amazon Location device position events arrive on the EventBridge default bus with source: ["aws.geo"] and detail-type: ["Location Device Position Event"]. In this model, the Lambda function is invoked for each incoming event.

Analytics 116

Analytics IoT Metadata Internet of Things 116

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

AWS Big Data

APRIL 2, 2024

You can use Amazon Data Firehose to aggregate and deliver log events from your applications and services captured in Amazon CloudWatch Logs to your Amazon Simple Storage Service (Amazon S3) bucket and Splunk destinations, for use cases such as data analytics, security analysis, application troubleshooting etc.

Metadata 105

Metadata Marketing Analytics Data Transformation 105

AWS Big Data

JUNE 6, 2023

Furthermore, it allows for necessary actions to be taken, such as rectifying errors in the data source, refining data transformation processes, and updating data quality rules. An EventBridge rule receives an event notification from the AWS Glue Data Quality evaluations including the results.

Data Quality 89

Data Quality Metrics Data-driven Visualization 89

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 97

Analytics Data Warehouse Metrics Big Data 97

DataKitchen

DECEMBER 9, 2022

By providing real-time visibility into the performance and behavior of data-related systems, DataOps observability enables organizations to identify and address issues before they become critical, and to optimize their data-related workflows for maximum efficiency and effectiveness.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

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. In other words, it measures the time between when data is expected and the moment when it is readily available for use. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 94

Cost-Benefit IoT Data Warehouse Manufacturing 94

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

AWS Big Data

MARCH 9, 2023

Additionally, there are major rewrites to deliver developer-focused improvements, including static type checking, enhanced runtime validation, strong consistency in call patterns, and optimized event chaining. is modernized by using promises for all actions, so developers can use async and await functions for better event management.

Slice and Dice 94

Slice and Dice Dashboards Analytics Interactive 94

AWS Big Data

MAY 16, 2023

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network).

Dashboards 92

Dashboards Statistics Data Collection Business Intelligence 92

Cloudera

OCTOBER 8, 2024

This service supports a range of optimized AI models, enabling seamless and scalable AI inference. By leveraging the NVIDIA NeMo platform and optimized versions of open-source models like Llama 3 and Mistral, businesses can harness the latest advancements in natural language processing, computer vision, and other AI domains.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

Cloudera

JUNE 1, 2021

Our customers must also have secure access to their data from anywhere – from on-premises to hybrid clouds and multiple public clouds. We must integrate and optimize the end-to-end data lifecycle for our customers, empowering them to focus on what really matters – extracting value from their data.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

AWS Big Data

APRIL 27, 2023

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance.

Data Lake 88

Data Lake Snapshot Optimization Data Transformation 88

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 83

Reporting Metrics Optimization Data Lake 83

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

AUGUST 8, 2024

Oracle GoldenGate for Oracle Database and Big Data adapters Oracle GoldenGate is a real-time data integration and replication tool used for disaster recovery, data migrations, high availability. GoldenGate provides special tools called S3 event handlers to integrate with Amazon S3 for data replication.

Analytics 105

Analytics Big Data Software Data Integration 105

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 serverless architecture features auto scaling, high availability, and a pay-as-you-go billing model to increase agility and optimize costs.

Visualization 116

Visualization Dashboards Data-driven Gap analysis 116

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. 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.

Dashboards 90

Dashboards Optimization Data Lake Cost-Benefit 90

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. In the Designer, you have the ability to start and stop each step of the data pipeline, resulting in events being queued up in the connections that link the processing steps together.

Testing 84

Testing Publishing Metadata Interactive 84

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. Shashank Tewari is a Senior Technical Account Manager at AWS.

Data Warehouse 109

Data Warehouse Analytics Data Lake Data Science 109

Cloudera

OCTOBER 14, 2020

YuniKorn is designed for Big Data app workloads, and it natively supports to run Spark/Flink/Tensorflow, etc efficiently in K8s. YuniKorn is optimized for performance, it is suitable for high throughput and large scale environments. YuniKorn scheduler provides an optimal solution to manage resource quotas by using resource queues.

Machine Learning 118

Machine Learning Management Big Data Optimization 118

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

It’s a pantry because all the data one needs is readily available and easily accessible, with labels that are immediately recognized and understood by the users of the application. In tech speak, this means the semantic layer is optimized for the intended audience.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

AWS Big Data

SEPTEMBER 6, 2023

Stored procedures are commonly used to encapsulate logic for data transformation, data validation, and business-specific logic. It inserts a record in the procedure_log table in the event of an exception. It also has an EXCEPTION block and inserts a record in the procedure_log table in the event of an exception.

Data Warehouse 113

Data Warehouse Insurance Statistics Software 113

AWS Big Data

JANUARY 27, 2023

As part of the solution workflow, EventBridge receives an event for each PCA solution analysis output file. Kinesis Data Firehose uses Lambda to perform data transformation and compression, storing the file in a compressed columnar format (Parquet) in the target S3 bucket. step 3) on the Amazon S3 console.

Analytics 71

Analytics Reporting Dashboards Visualization 71

AWS Big Data

OCTOBER 12, 2023

With EMR Serverless, you don’t have to configure, optimize, secure, or operate clusters to run applications with these frameworks. You can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements.

Big Data 124

Big Data Data-driven Management Visualization 124

Sisense

MAY 11, 2021

When it comes to data modeling, function determines form. Let’s say you want to subject a dataset to some form of anomaly detection; your model might take the form of a singular event stream that can be read by an anomaly detection service. filling in nulls, changing time zones, formatting strings, conditional logic, etc.)

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 59

Cost-Benefit Informatics Optimization Management 59

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. We can use knowledge of the data to optimize the join by filtering the data we really need.

Visualization 95

Visualization Cost-Benefit Data Quality Publishing 95

AWS Big Data

FEBRUARY 26, 2024

When you start the process of designing your data model for Amazon Keyspaces, it’s essential to possess a comprehensive understanding of your access patterns, similar to the approach used in other NoSQL databases. Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery.

Dashboards 78

Dashboards Testing Metrics Optimization 78

AWS Big Data

JANUARY 17, 2024

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. By identifying these changes, the query engine can optimize the query to process only the relevant data, significantly reducing the processing time and resource requirements.

Data Lake 112

Data Lake Snapshot Big Data Data-driven 112

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

SEPTEMBER 13, 2024

Finally, CFM uses an AWS Graviton architecture to optimize even more cost and performance (as highlighted in the screenshot below). Another advantage was improved security, particularly the ability to contain the potential impact area in the event of credential leaks or account compromises.

Interactive 93

Interactive Strategy Cost-Benefit Data Governance 93

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