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

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

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 90

Analytics IoT Metadata Internet of Things 90

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

AWS Big Data

JULY 31, 2023

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.” This concludes creating data sources on the AWS Glue job canvas. Choose Confirm.

Sales 52

Sales Data Warehouse Visualization Testing 52

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 translate their documents, presentations, tables, etc. This is one of the main diagnostic tests. into structured knowledge that can be processed by machines.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. This variety can result in a lack of standardization, leading to data duplication and inconsistency.

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

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

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. It does not exist in the code.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. Take Grammarly as an example: This popular program checks the grammar, tone, and style of documents. Getting this AI properly trained required a huge learning dataset with countless documents that were tagged according to specific criteria. The perfect fit.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

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 Business Intelligence 52

AWS Big Data

OCTOBER 31, 2023

If you’re testing on a different Amazon MWAA version, update the requirements file accordingly. For testing purposes, you can choose Add permissions and add the managed AmazonS3FullAccess policy to the user instead of providing restricted access. Modify the policy document with the DESC STORAGE INTEGRATION output values you recorded.

Data Processing 86

Data Processing Management Publishing Testing 86

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 125

Machine Learning Visualization IoT Digital Transformation 125

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Data Transformation in the Modern Data Stack. How did the data transform exactly?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. 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.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

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

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 99

Data Lake Management Metrics Data Warehouse 99

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

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

Jet Global

MAY 1, 2023

Modern Data Sources Painlessly connect with modern data such as streaming, search, big data, NoSQL, cloud, document-based sources. Quickly link all your data from Amazon Redshift, MongoDB, Hadoop, Snowflake, Apache Solr, Elasticsearch, Impala, and more. addresses). Read carefully. Build your first set of reports.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52