AWS Big Data

OCTOBER 14, 2024

Writing SQL queries requires not just remembering the SQL syntax rules, but also knowledge of the tables metadata, which is data about table schemas, relationships among the tables, and possible column values. Generative AI models can translate natural language questions into valid SQL queries, a capability known as text-to-SQL generation.

Metadata 104

Metadata Data Lake Modeling Data Warehouse 104

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. Data Science – Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

DataKitchen

JULY 27, 2023

Azure Databricks, a big data analytics platform built on Apache Spark, performs the actual data transformations. The cleaned and transformed data can then be stored in Azure Blob Storage or moved to Azure Synapse Analytics for further analysis and reporting. Some tools are excellent for batch processing (e.g.,

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. 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

datapine

SEPTEMBER 29, 2022

Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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. Create tests. Run the factory.

Testing 152

Testing Dashboards Measurement Experimentation 152

datapine

MAY 2, 2023

Your Chance: Want to test a professional logistics analytics software? Use our 14-days free trial today & transform your supply chain! Big data enables automated systems by intelligently routing many data sets and data streams. Your Chance: Want to test a professional logistics analytics software?

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 169

Testing Risk Data Processing Statistics 169

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics includes the tools and techniques used to perform data analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam is designed for seasoned and high-achiever data science thought and practice leaders.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

AWS Big Data

JULY 18, 2024

As part of the migration, reconsider your data model. In examining your data model, you can find efficiencies that dramatically improve your search latencies and throughput. Poor data modeling doesn’t only result in search performance problems but extends to other areas.

Dashboards 113

Dashboards Testing Data-driven Visualization 113

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 126

Data Warehouse Testing Data Quality Reporting 126

DataKitchen

OCTOBER 25, 2022

The goal of DataOps Observability is to provide visibility of every journey that data takes from source to customer value across every tool, environment, data store, data and analytic team, and customer so that problems are detected, localized and raised immediately. That data then fills several database tables.

Testing 130

Testing Data-driven Visualization Dashboards 130

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 130

Testing Risk Data Processing Statistics 130

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

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.

Analytics 111

Analytics Dashboards Metadata Data Warehouse 111

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

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. Dependency analysis Understanding dependencies between objects is crucial for a successful migration.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

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 95

Data Integration Snapshot Testing Visualization 95

Occam's Razor

OCTOBER 19, 2010

If you can show ROI on a DW it would be a good use of your money to go with Omniture Discover, WebTrends Data Mart, Coremetrics Explore. If you have evolved to a stage that you need behavior targeting then get Omniture Test and Target or Sitespect. Experimentation and Testing Tools [The "Why" – Part 1]. and embrace Multiplicity.

Analytics 136

Analytics Testing Measurement Optimization 136

Cloudera

JUNE 24, 2024

The complexities of modern data workflows often translate into countless hours spent coding, debugging, and optimizing models. Recognizing this pain point, we set out to redefine the data science experience with AI-driven innovation. This practical support speeds up project initiation and maintains consistent coding practices.

Machine Learning 72

Machine Learning Data Science Data-driven Testing 72

Cloudera

OCTOBER 13, 2020

Data Warehouse – in addition to a number of performance optimizations, DW has added a number of new features for better scalability, monitoring and reliability to enable self-service access with security and performance . Predict – Data Engineering (Apache Spark). New Services. Learn More, Keep in Touch.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

Smarten

MAY 13, 2024

Incorporate PMML Integration Within Augmented Analytics to Easily Manage Predictive Models! PMML is Predictive Model Markup Language. It is an interchange format that provides a method by which analytical applications and software can describe and exchange predictive models. So, what is PMML Integration?

Predictive Modeling 64

Predictive Modeling Data mining Predictive Analytics Modeling 64

AWS Big Data

AUGUST 6, 2024

Amazon Redshift ML is a feature of Amazon Redshift that enables you to build, train, and deploy machine learning (ML) models directly within the Redshift environment. Generative AI models can derive new features from your data and enhance decision-making. Create a materialized view to load the raw streaming data.

Data Warehouse 101

Data Warehouse Data-driven Modeling Internet of Things 101

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. Feature Engineering Terminology and Motivation.

Testing 68

Testing Modeling Interactive Measurement 68

Cloudera

OCTOBER 8, 2024

This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Enterprise developers began exploring proof of concepts (POCs) for generative AI applications, leveraging API services and open models such as Llama 2 and Mistral. By 2023, the focus shifted towards experimentation.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

AWS Big Data

JANUARY 30, 2025

Our approach The migration initiative consisted of two main parts: building the new architecture and migrating data pipelines from the existing tool to the new architecture. Often, we would work on both in parallel, testing one component of the architecture while developing another at the same time.

Data Warehouse 53

Data Warehouse Data Architecture Machine Learning Data Transformation 53

CIO Business Intelligence

JUNE 13, 2022

According to Evanta’s 2022 CIO Leadership Perspectives study, CIOs’ second top priority within the IT function is around data and analytics, with CIOs seeing advancing organizational use of data as key to reaching enterprise objectives. To get there, Angel-Johnson has embarked on a master data management initiative.

IT 144

IT Digital Transformation Internet of Things Strategy 144

Cloudera

DECEMBER 21, 2021

Cloudera’s Shared Data Experience (SDX) provides all these capabilities allowing seamless data sharing across all the Data Services including CDE. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. . Test Drive CDP Pubic Cloud.

Snapshot 118

Snapshot Data-driven Optimization Data Architecture 118

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

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 110

Enterprise Data Warehouse Data Lake Optimization 110

AWS Big Data

AUGUST 26, 2024

Duplicating data from a production database to a lower or lateral environment and masking personally identifiable information (PII) to comply with regulations enables development, testing, and reporting without impacting critical systems or exposing sensitive customer data. PII detection and scrubbing.

Visualization 115

Visualization Metadata Data Transformation Testing 115

Cloudera

FEBRUARY 8, 2021

Development Environment for Data Scientists, Isolated, Containerized, and Elastic. Production ML Toolkit – Deploying, Serving, Monitoring, and Governance of ML models. Simple, drag-and-drop building of dashboards and apps with Cloudera Data Visualization. Now, let’s start testing our model! and run it.

Machine Learning 75

Machine Learning Statistics Dashboards Modeling 75

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

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 84

Dashboards Testing Metrics Optimization 84

AWS Big Data

MARCH 16, 2023

A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models. Whenever models are created or modified, a dbt Cloud CI job is triggered to test the models by materializing the models in Amazon Redshift.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

Insight

APRIL 8, 2020

In some cases, they work to deploy data science models into production with an eye towards optimization, scalability and maintainability. Data architects and data modelers who specialize in areas such as schema design, identifying query access patterns and building and maintaining data warehouses.

Data Warehouse 96

Data Warehouse Cost-Benefit Software Optimization 96