AWS Big Data

NOVEMBER 9, 2023

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 112

Data Warehouse Testing Data Quality Reporting 112

AWS Big Data

OCTOBER 18, 2023

They use various AWS analytics services, such as Amazon EMR, to enable their analysts and data scientists to apply advanced analytics techniques to interactively develop and test new surveillance patterns and improve investor protection. starts_with(OutputKey,'eksclusterEKSConfig')].OutputValue" OutputKey=='HiveSecretName'].OutputValue"

Big Data 84

Big Data Data Processing Interactive Testing 84

Cloudera

OCTOBER 19, 2021

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. It was critical to make the interactions as intuitive as possible to avoid slowing down the flow of the user.

Data Transformation 119

Data Transformation Interactive Machine Learning Testing 119

AWS Big Data

NOVEMBER 15, 2023

Each CDH dataset has three processing layers: source (raw data), prepared (transformed data in Parquet), and semantic (combined datasets). It is possible to define stages (DEV, INT, PROD) in each layer to allow structured release and test without affecting PROD.

Dashboards 101

Dashboards Analytics Metadata Data Warehouse 101

datapine

SEPTEMBER 29, 2022

from the business interactions), but if not available, then through confirmation techniques of an independent nature. It will indicate whether data is void of significant errors. Also known as data validation, integrity refers to the structural testing of data to ensure that the data complies with procedures.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Cloudera

JULY 21, 2022

As creators and experts in Apache Druid, Rill understands the data store’s importance as the engine for real-time, highly interactive analytics. Cloudera Data Warehouse). Efficient batch data processing. Complex data transformations. Figure 1: Rill and Cloudera Architecture. Apache Hive. Windowing functions.

Metrics 86

Metrics Slice and Dice Data Warehouse Dashboards 86

AWS Big Data

JULY 26, 2023

To grow the power of data at scale for the long term, it’s highly recommended to design an end-to-end development lifecycle for your data integration pipelines. The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop?

Data Integration 73

Data Integration Snapshot Testing Visualization 73

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This will enable right-sizing the Redshift data warehouse to meet workload demands cost-effectively. Additional considerations – Factor in additional tasks beyond schema conversion.

Data Warehouse 92

Data Warehouse KPI Optimization Cost-Benefit 92

AWS Big Data

OCTOBER 11, 2023

We introduce you to Amazon Managed Service for Apache Flink Studio and get started querying streaming data interactively using Amazon Kinesis Data Streams. Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources.

Management 110

Management Metadata Analytics Dashboards 110

AWS Big Data

OCTOBER 14, 2024

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes.

Metadata 82

Metadata Data Lake Modeling Data Warehouse 82

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. Create a DataBrew recipe Start by registering the data store for the claims file.

Visualization 83

Visualization Cost-Benefit Data Quality Publishing 83

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. Jason: What’s the value of using dbt with the data catalog ?

Metrics 52

Metrics Dashboards Sales Reporting 52

Cloudera

AUGUST 8, 2022

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). In the final stage of our ETL pipeline, we load new data into this partition. Using CDW with Iceberg.

Snapshot 93

Snapshot Data Warehouse Machine Learning Cost-Benefit 93

Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? The perfect fit.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Domino Data Lab

AUGUST 20, 2019

The problem is that a new unique identifier of a test example won’t be anywhere in the tree. Feature extraction means moving from low-level features that are unsuitable for learning—practically speaking, we get poor testing results—to higher-level features which are useful for learning. Separate out a hold-out test set.

Testing 68

Testing Modeling Interactive Measurement 68

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 86

Management Interactive Metadata Publishing 86

Alation

JANUARY 17, 2023

As data science is growing in popularity and importance , if your organization uses data science, you’ll need to pay more attention to picking the right tools for this. An example of a data science tool is Dataiku. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

IBM Big Data Hub

JANUARY 18, 2023

For these workloads, data lake vendors usually recommend extracting data into flat files to be used solely for model training and testing purposes. This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. Each node can be different from the others.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

NOVEMBER 16, 2023

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge of and adherence to battle-tested best practices, and using the right tools and features in the right scenario. Data Vault 2.0

Enterprise 91

Enterprise Data Warehouse Data Lake Optimization 91

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. This solution includes a Lambda function that continuously updates the Amazon Location tracker with simulated location data from fictitious journeys.

Analytics 102

Analytics IoT Metadata Internet of Things 102

Cloudera

OCTOBER 14, 2020

Apache Spark unifies batch processing, real-time processing, stream analytics, machine learning, and interactive query in one-platform. The Test and Development queue have fixed resource limits. Background. Why choose K8s for Apache Spark. All other queues are only limited by the size of the cluster. Acknowledgments.

Machine Learning 118

Machine Learning Management Big Data Optimization 118

AWS Big Data

JUNE 29, 2023

In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities. Kinesis Data Analytics Studio allows us to create a notebook, which is a web-based development environment.

Data Analytics 78

Data Analytics Analytics IoT Data Lake 78

AWS Big Data

FEBRUARY 21, 2023

Solutions Architect – AWS SafeGraph is a geospatial data company that curates over 41 million global points of interest (POIs) with detailed attributes, such as brand affiliation, advanced category tagging, and open hours, as well as how people interact with those places. These versions are all exposed to users via their UI.

Cost-Benefit 59

Cost-Benefit Informatics Optimization Management 59

IBM Big Data Hub

JULY 17, 2023

While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases. offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Ontotext

APRIL 4, 2019

Within a large enterprise, there is a huge amount of data accumulated over the years – many decisions have been made and different methods have been tested. This is one of the main diagnostic tests. The doctor needs to know how to collect the data from this image. This process requires great expertise.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

DataRobot Blog

APRIL 4, 2022

Before the data is put into the model comes a process called feature engineering – transforming the original data columns to impose certain business assumptions or simply increase model accuracy. The classical approach is to assume the adstock function (typically linear ) and test out various values of ?

Machine Learning 52

Machine Learning Sales Measurement ROI 52

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 110

Data Lake Management Metrics Data Warehouse 110

CIO Business Intelligence

AUGUST 7, 2024

The initiative has enhanced coordination, as automation APIs facilitate interaction with security tools as well as streamline coordination and enhance mitigation responses. This is a new way to interact with the web and search. This enabled the team to expose the technology to a small group of senior leaders to test.

IT 119

IT Insurance Cost-Benefit Testing 119

FineReport

MARCH 31, 2024

Through meticulous testing and research, we’ve curated a list of the ten best BI tools, ensuring accessibility and efficacy for businesses of all sizes. In essence, the core capabilities of the best BI tools revolve around four essential functions: data integration, data transformation, data visualization, and reporting.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Cloudera

OCTOBER 11, 2021

Modak Nabu relies on a framework of “Botworks”, a series of micro-jobs to accomplish various data transformation steps from ingestion to profiling, and indexing. Cloudera Data Engineering within CDP provides : Fully managed Spark-on-Kubernetes service that hides the complexity running production DE workloads at scale.

Data Lake 94

Data Lake Cost-Benefit Data-driven Dashboards 94

AWS Big Data

DECEMBER 21, 2023

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. The data products from the Business Vault and Data Mart stages are now available for consumers.

Data Lake 96

Data Lake Data Warehouse B2B Data-driven 96

AWS Big Data

APRIL 5, 2023

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Yes—but basic dashboards won’t be enough.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 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