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. The Lambda function is responsible for converting the data quality metrics and dispatching them to the designated email addresses via Amazon SNS.

Data Quality 75

Data Quality Metrics Data-driven Visualization 75

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 106

Data Warehouse Testing Data Quality Reporting 106

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 130

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 130

FineReport

MARCH 7, 2024

Data Analysis Report (by FineReport ) Note: All the data analysis reports in this article are created using the FineReport reporting tool. Leveraging the advanced enterprise-level web reporting tool capabilities of FineReport , we empower businesses to achieve genuine data transformation. Try FineReport Now 1.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

AWS Big Data

APRIL 11, 2023

With the proliferation of IoT devices and the abundance of data generated by them, it has become possible to collect real-time data on inventory levels, customer behavior, and other key metrics. In the inventory management and forecasting solution, AWS Glue is recommended for data transformation.

Forecasting 77

Forecasting Management IoT Data-driven 77

AWS Big Data

FEBRUARY 6, 2023

Let’s look at some key metrics. After analyzing YARN logs by various metrics, you’re ready to design future EMR architectures. His area of interests are data lakes and cloud modern data architecture delivery. Kalen Zhang was the Global Segment Tech Lead of Partner Data and Analytics at AWS.

Dashboards 77

Dashboards Optimization Data Lake Cost-Benefit 77

Cloudera

MARCH 14, 2023

A critical feature for every developer however is to get instantaneous feedback like configuration validations or performance metrics, as well as previewing data transformations for each step of their data flow. Test Sessions provide this functionality by provisioning compute resources on the fly within minutes.

Testing 87

Testing Publishing Metadata Interactive 87

AWS Big Data

FEBRUARY 26, 2024

You simply configure your data sources to send information to OpenSearch Ingestion, which then automatically delivers the data to your specified destination. Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery.

Dashboards 63

Dashboards Testing Metrics Optimization 63

DataKitchen

OCTOBER 5, 2021

The data organization wants to run the Value Pipeline as robustly as a six sigma factory, and it must be able to implement and deploy process improvements as rapidly as a Silicon Valley start-up. The data engineer builds data transformations. Their product is the data.

Testing 152

Testing Dashboards Measurement Experimentation 152

AWS Big Data

FEBRUARY 6, 2023

The results of the log analyzer reveal Hadoop workload insights with various views and metrics of the Hadoop applications shown in Amazon QuickSight dashboards, which leads to the design of a future EMR cluster. His area of interests are data lakes and cloud modern data architecture delivery.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MAY 16, 2023

Data collection and processing are handled by a third-party smart sensor manufacturer application residing in Amazon Virtual Private Cloud (Amazon VPC) private subnets behind a Network Load Balancer. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

Dashboards 79

Dashboards Statistics Data Collection Business Intelligence 79

DataRobot Blog

MARCH 10, 2022

The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against. This task may require complex joins, aggregations, filtering, window functions, and many other data transformations against extremely large-scale data sets.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

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). So go ahead.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

OCTOBER 11, 2023

In this post, we discuss ways to modernize your legacy, on-premises, real-time analytics architecture to build serverless data analytics solutions on AWS using Amazon Managed Service for Apache Flink. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

Management 106

Management Metadata Analytics Dashboards 106

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Data Transformation in the Modern Data Stack.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Ontotext

APRIL 4, 2019

They have different metrics for judging whether some content is interesting or not. Milena Yankova : The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. Milena Yankova : That’s a very interesting question.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

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 86

Dashboards Visualization Metrics Data Transformation 86

CIO Business Intelligence

JUNE 23, 2022

The challenge is to capture source of the data correctly from the outset and ensure data quality does not degrade when moving across the data supply-chain. A key supply chain management metric used to evaluate the performance of physical supply chains is OTIF – On-Time-In-Full. Supply chain complexity.

Data Quality 97

Data Quality Key Performance Indicator Metrics KPI 97

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

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

Sisense

AUGUST 6, 2020

An obvious mechanical answer is: use relevance as a metric. Another important method is to benchmark existing metrics. Know the limitations of your existing dataset and answer these questions: What categories of data are there? What data transformations are needed from your data scientists to prepare the data?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

O'Reilly on Data

JANUARY 17, 2023

In the past they understood the APIs of TensorFlow and Torch to build models by hand; today they are fluent in the autoML vendor’s APIs to train models, and they understand how to review the metrics. The second is the experienced ML professional who really knows how to build and tune models. It does not exist in the code.

Machine Learning 326

Machine Learning Predictive Modeling Software Modeling 326

Cloudera

JUNE 17, 2022

The NiFi flow behind the Inbound Connection can not only receive data and forward it to a Kafka topic, but can perform schema validation, format conversions, and data transformation, as well as routing, filtering, and enriching the data.

Cost-Benefit 97

Cost-Benefit IoT Data Warehouse Manufacturing 97

AWS Big Data

JULY 20, 2023

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

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 84

Data Lake Dashboards Metrics Metadata 84

Alation

DECEMBER 7, 2021

This platform should: Connect to diverse data sources (on-prem, hybrid, legacy, or modern). Extract data quality information. Monitor data anomalies and data drift. Track how data transforms, noting unexpected changes during its lifecycle. Alation’s Data Catalog: Built-in Data Quality Capabilities.

Data Quality 52

Data Quality Data-driven Metrics Dashboards 52

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. This means establishing and enforcing policies and processes, standards, roles, and metrics. Why Is Data Governance in Healthcare Important? Dashboards are useful means to track such change.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

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. It’s not just a fear of change.

Testing 130

Testing Data-driven Visualization Dashboards 130

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. On the Runs tab, you can keep track of the process and see detailed job metrics using the job ID link.

Visualization 84

Visualization Cost-Benefit Data Quality Interactive 84

Sisense

MAY 11, 2021

Reporting Reporting contains the flattest and most cleaned version of our data. It often will collapse the metrics in a fact table to the level of a single dimension through a form of aggregation or lookback window. Importantly, both workflows for data analytics are supported by a set of data models that follow the same data pipeline.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

DataRobot Blog

APRIL 4, 2022

Media data (usually weekly): media costs, media ratings generated (TVRs, magazine copies, digital impressions, likes, shares, etc.), The standard practice is that the data should be aggregated into a weekly format and span at least the last two to three years (ideally around five years). Classical Modeling Considerations.

Machine Learning 52

Machine Learning Sales Measurement ROI 52

Ontotext

DECEMBER 9, 2020

Are you having difficulty joining your knowledge graph APIs with other data sources? Maybe you spend an inordinate amount of time and effort managing operational concerns, deployments, monitoring, metrics and log collation? This leads to lots of small data fetches to/from GraphDB over the network.

Modeling 130

Modeling Management Optimization Metrics 130

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 55

Cost-Benefit Informatics Optimization Management 55

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 104

Data Lake Management Metrics Data Warehouse 104

Occam's Razor

OCTOBER 19, 2010

Mongoose Metrics ~ ifbyphone. I know Mongoose Metrics a bit more and have been impressed with their solution and evolution over the last couple of years. Twitter to me is a proxy of how data collection is changing and what the future of relevant metrics might look like. Mongoose Metrics. AnalyzeWords. LivePerson.

Analytics 135

Analytics Testing Measurement Optimization 135

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. Multiple Metrics for Success. At GSK, success is all about adoption.

Measurement 246

Measurement Metrics Data-driven Testing 246