AWS Big Data

JULY 26, 2023

Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions. Are there recommended approaches to provisioning components for data integration?

Data Integration 97

Data Integration Snapshot Testing Visualization 97

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 279

Machine Learning Software Metadata Testing 279

AWS Big Data

JANUARY 9, 2025

Iceberg offers distinct advantages through its metadata layer over Parquet, such as improved data management, performance optimization, and integration with various query engines. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

AWS Big Data

JULY 19, 2023

You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model. Amazon Redshift provides built-in features to accelerate the process of modeling, orchestrating, and reporting from a dimensional model. Declare the grain of your data.

Modeling 96

Modeling Sales Data Warehouse Snapshot 96

AWS Big Data

OCTOBER 21, 2024

When dealing with third-party data sources, AWS Data Exchange simplifies the discovery, subscription, and utilization of third-party data from a diverse range of producers or providers. As a producer, you can also monetize your data through the subscription model using AWS Data Exchange.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

CIO Business Intelligence

AUGUST 16, 2023

ChatGPT is capable of doing many of these tasks, but the custom support chatbot is using another model called text-embedding-ada-002, another generative AI model from OpenAI, specifically designed to work with embeddings—a type of database specifically designed to feed data into large language models (LLM).

Modeling 98

Modeling Enterprise Cost-Benefit Data Science 98

DataKitchen

APRIL 28, 2021

In Figure 1, the nodes could be sources of data, storage, internal/external applications, users – anything that accesses or relates to data. Data fabrics provide reusable services that span data integration, access, transformation, modeling, visualization, governance, and delivery.

Statistics 246

Statistics Optimization Data Analytics Technology 246

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. They create reliable, consistent and communicable models for representing data. Schemas are powerful.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

DataKitchen

DECEMBER 9, 2022

The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes. ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

DataKitchen

OCTOBER 20, 2023

The Solution: ‘Payload’ Data Journeys Traditional Data Observability usually focuses on a ‘process journey,’ tracking the performance and status of data pipelines. ’ It assigns unique identifiers to each data item—referred to as ‘payloads’—related to each event.

Insurance 173

Insurance Metadata Data-driven Data Quality 173

DataKitchen

SEPTEMBER 21, 2023

.’ It’s not just about playing detective to discover where things went wrong; it’s about proactively monitoring your entire data journey to ensure everything goes right with your data. What is Data in Place? ” For example, these tools may offer metadata-based notifications.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

Ontotext

AUGUST 24, 2023

The solution is choosing one of the standard provenance models. Standard provenance models Graph Replace is probably the most straightforward model. Trade-offs of the standard provenance models Graph Replace is fast and simple to implement and we recommend it to people with batch updates. Persistent or non-persistent IDs?

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

AWS Big Data

MAY 23, 2024

In today’s data-driven world, organizations often deal with data from multiple sources, leading to challenges in data integration and governance. This process is crucial for maintaining data integrity and avoiding duplication that could skew analytics and insights. Choose Create notebook.

Machine Learning 119

Machine Learning Interactive Recreation/Entertainment Data Integration 119

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing. Choose Create connection. Choose Next.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Ontotext

JULY 29, 2021

The Semantic Web started in the late 90’s as a fascinating vision for a web of data, which is easy to interpret by both humans and machines. One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JULY 17, 2019

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Smart Data Collective

JUNE 1, 2022

As stated earlier, data is the digital gold in the modern era. Your business’s success or failure depends on your collection and processing of relevant data. Companies use data to develop their marketing and pricing models and gain access to a larger consumer base. Data integrity is important.

Revenue Optimization 145

Revenue Optimization Measurement Marketing Interactive 145

Smart Data Collective

NOVEMBER 10, 2021

Without this knowledge, the result can be compromised data or ruined data integrity. Other common issues include duplicate data, which may need to be merged; obsolete data, which will need to be deleted before conversion; and incorrect data, which may result in the need for a manual fix.

Testing 137

Testing Data Integration Software Modeling 137

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. To create an AWS HealthLake data store, refer to Getting started with AWS HealthLake. reference", SUBSTRING(a."patient"."reference",

Data Analytics 119

Data Analytics Analytics Data Warehouse Data Lake 119

AWS Big Data

MAY 3, 2023

These two tasks (building data lakes or data warehouses and application modernization) involve data movement, which uses an extract, transform, and load (ETL) process. Developers would also need to build this quickly to migrate the data. Developers can use AWS Glue Studio to efficiently create such data pipelines.

Data Lake 114

Data Lake Data Warehouse Data-driven Optimization 114

AWS Big Data

NOVEMBER 29, 2023

The dbt-glue adapter democratized access for dbt users to data lakes, and enabled many users to effortlessly run their transformation workloads on the cloud with the serverless data integration capability of AWS Glue. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

FineReport

JUNE 11, 2021

According to the definition, business intelligence and analytics refer to the data management solutions implemented in companies to collect, analyze and drive insights from data. By contrast, business analytics may use historical data to predict what may happen in the future or how the organization will move forward.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

erwin

APRIL 4, 2022

If you’re a long-time erwin ® Data Modeler by Quest ® customer, you might be asking yourself, “What happened to the release naming convention of erwin Data Modeler?” In 2021 erwin Data Modeler released 2021R1. What’s new in erwin Data Modeler R12.0? DevOps GitHub integration via Mart.

Modeling 52

Modeling Data Processing Data-driven Big Data 52

datapine

NOVEMBER 11, 2021

This data is usually saved in different databases, external applications, or in an indefinite number of Excel sheets which makes it almost impossible to combine different data sets and update every source promptly. BI tools aim to make data integration a simple task by providing the following features: a) Data Connectors.

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213

AWS Big Data

AUGUST 15, 2024

The Central IT team manages a unified Redshift data warehouse, handling all data integration, processing, and maintenance. Business units access clean, standardized data. This model enables the units to focus on insights, with costs aligned to actual consumption. In this post, we use three AWS accounts.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

AWS Big Data

MAY 21, 2024

A significant part of this phase involved the innovative process of data flattening, a technique crucial for managing complex product data. This product is linked to several related tables: one for basic details like model number and manufacturer, another for pricing, and another for features such as energy efficiency and capacity.

Manufacturing 111

Manufacturing Sales Optimization Data Processing 111

CIO Business Intelligence

MAY 18, 2022

They range from organizational architects who define business and operating models to projects, platforms, and digital architects. That may require, for example, an analysis of ERP systems to understand all the dependencies and functions that reference a bill of materials, he says.

Enterprise 122

Enterprise Measurement Data-driven Software 122

IBM Big Data Hub

NOVEMBER 14, 2023

But few organizations have made the strategic shift to managing “data as a product.” ” This data management means applying product development practices to data. Serve: Data products are discoverable and consumed as services, typically via a platform.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

AWS Big Data

SEPTEMBER 20, 2023

With this functionality, you’re empowered to focus on extracting valuable insights from their data, while AWS Glue handles the infrastructure heavy lifting using a serverless compute model. To get started today, refer to Developing AWS Glue jobs with Notebooks and Interactive sessions. Big Data Architect.

Interactive 111

Interactive Visualization Measurement Data Architecture 111

AWS Big Data

MARCH 15, 2023

They wanted to develop a simple incremental data processing pipeline without having to update the entire database each time the pipeline ran. The Apache Hudi framework allowed the Infomedia team to maintain a golden reference dataset and capture changes so that the downstream database could be incrementally updated in a short timeframe.

Cost-Benefit 94

Cost-Benefit Data Processing Optimization Data-driven 94

AWS Big Data

DECEMBER 21, 2023

OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration. Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue.

Analytics 111

Analytics IT Data Lake Visualization 111

AWS Big Data

NOVEMBER 10, 2023

As a result of utilizing the Amazon Redshift integration for Apache Spark, developer productivity increased by a factor of 10, feature generation pipelines were streamlined, and data duplication reduced to zero. You can gain performance improvements by using the default Parquet format used for unloading with this integration.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111