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 107

Management Metadata Analytics Dashboards 107

Octopai

OCTOBER 6, 2022

Moving is generally a high-stress event for multiple reasons: Finding a reasonable mortgage offer and getting approved for it Concern that you won’t have enough money to cover unexpected expenses Packing up everything you own… and then unpacking it Hoping all your possessions make it to their destination without getting broken or lost.

Testing 52

Testing Visualization Data Transformation Strategy 52

Sisense

AUGUST 28, 2020

All this contributes to your overall data integrity profile. Logical data integrity is designed to guard against human error. We’ll explore this concept in detail in the testing section below. Data integrity: A process and a state. There are two means for ensuring data integrity: process and testing.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

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 126

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 126

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. This allows for easy access and analysis of these events.

Dashboards 64

Dashboards Testing Metrics Optimization 64

AWS Big Data

APRIL 25, 2023

On many occasions, they need to apply business logic to the data received from the source SaaS platform before pushing it to the target SaaS platform. AnyCompany’s marketing team hosted an event at the Anaheim Convention Center, CA. The marketing team created leads based on the event in Adobe Marketo. Let’s take an example.

Sales 74

Sales Visualization Software Marketing 74

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 Sales 52

datapine

SEPTEMBER 29, 2022

Also known as data validation, integrity refers to the structural testing of data to ensure that the data complies with procedures. 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 Quality 241

Data Quality Metrics Data-driven Management 241

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 85

Metrics Slice and Dice Data Warehouse Dashboards 85

AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

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 72

Reporting Metrics Optimization Data Lake 72

AWS Big Data

DECEMBER 21, 2023

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

AWS Big Data

JULY 6, 2023

It has not been specifically designed for heavy data transformation tasks. To load the time series for a specific point into a pandas data frame, you can use the awswrangler library from your Python code: import awswrangler as wr import pandas as pd # Retrieving the data directly from Amazon S3 df = wr.s3.read_parquet("s3://

Machine Learning 132

Machine Learning Visualization IoT Digital Transformation 132

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 88

Dashboards Visualization Metrics Data Transformation 88

Smart Data Collective

APRIL 29, 2020

The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Microsoft Azure.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

O'Reilly on Data

JANUARY 17, 2023

Upload your data, click through a workflow, walk away. If you’re a professional data scientist, you already have the knowledge and skills to test these models. Get your results in a few hours. Why would you want autoML to build models for you? It buys time and breathing room. And it made sense.

Machine Learning 321

Machine Learning Predictive Modeling Software Modeling 321

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 76

Data Lake Snapshot Optimization Data Transformation 76

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

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

AWS Big Data

JULY 31, 2023

You can examine various events from the stack creation process on the Events tab. Select the connection again and on the Actions menu, choose Test connection. Testing the connection can take approximately 1 minute. You will see the message “Successfully connected to the data store with connection blog-redshift-connection.”

Sales 52

Sales Data Warehouse Visualization Testing 52

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

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. Apache Spark is the engine that runs the jobs created on AWS Glue Studio.

Visualization 85

Visualization Cost-Benefit Data Quality Interactive 85

CIO Business Intelligence

JUNE 13, 2022

Angel-Johnson says she, too, has a heightened level of concern around security issues and more specifically data protection. I thought I was hired for digital transformation but what is really needed is a data transformation,” she says. To get there, Angel-Johnson has embarked on a master data management initiative.

IT 144

IT Digital Transformation Strategy Internet of Things 144

AWS Big Data

OCTOBER 31, 2023

Customers rely on data from different sources such as mobile applications, clickstream events from websites, historical data, and more to deduce meaningful patterns to optimize their products, services, and processes. If you’re testing on a different Amazon MWAA version, update the requirements file accordingly.

Data Processing 92

Data Processing Management Publishing Testing 92

Cloudera

OCTOBER 14, 2020

The Test and Development queue have fixed resource limits. YuniKorn is also compatible with the management commands and utilities, such as cordon nodes, retrieving events via kubectl, etc. Cloudera’s CDP platform offers Cloudera Data Engineering experience which is powered by Apache YuniKorn (Incubating). Acknowledgments.

Machine Learning 116

Machine Learning Management Big Data Optimization 116

AWS Big Data

FEBRUARY 6, 2023

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. The parser also has other capabilities, including sorting events by time, removing dedicates, and merging multiple logs. Choose Delete.

Dashboards 78

Dashboards Optimization Data Lake Cost-Benefit 78

DataRobot Blog

APRIL 4, 2022

More often than I would like to admit, I have heard the following phrase from a client: “We do not have the data for the five media campaigns we ran last year, but we have data for the other four. 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

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. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 76

Data Analytics Analytics IoT Data Lake 76

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. We minimized the time between the event (and what the journalist wanted to say about it) and the moment the reader or viewer could consume it.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

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

Peter James Thomas

OCTOBER 30, 2018

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. Establishing a regular Data Audit.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

Alation

OCTOBER 28, 2021

This, in turn, empowers data leaders to better identify and develop new revenue streams, customize patient offerings, and use data to optimize operations. These mandates ensure that PHA and PII data are protected and managed properly, so that patients are protected in the event of data breaches.

Data Governance 52

Data Governance Measurement Metrics Modeling 52

Jet Global

MAY 1, 2023

Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52