David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 311

Management Data Warehouse Data Quality Data Integration 311

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

Data Virtualization

FEBRUARY 22, 2023

Reading Time: 2 minutes The data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data.

Data Lake 52

Data Lake Data Warehouse Data Integration Management 52

Data Virtualization

FEBRUARY 22, 2023

Reading Time: 2 minutes The data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data.

Data Lake 52

Data Lake Data Warehouse Data Integration Management 52

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 89

Data Warehouse Data-driven Machine Learning B2B 89

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

Data Analytics Data Lake Data Warehouse Analytics 52

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Processing large amounts of raw data from various sources requires appropriate tools and solutions for effective data integration. Building an ETL pipeline using Apache […].

Data Integration 382

Data Integration Data Science Publishing Analytics 382

BizAcuity

APRIL 1, 2023

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

CIO Business Intelligence

JULY 18, 2022

Central to Byrdak’s multi-year transformation plan is the expansion of MealConnect, the first nationally available food rescue and sourcing platform, and a new data warehouse to anchor an analytics offering that helps food banks analyze and visualize their food sourcing and distribution data.

Data Warehouse 141

Data Warehouse Dashboards Reporting Manufacturing 141

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Data Virtualization

APRIL 7, 2022

As far back as 2011 Gartner proposed the concept of a logical data warehouse as a way to overcome some of the challenges organizations. The post Does Data Always Need to End Up in a Centralized Repository? Reading Time: 3 minutes This is an age-old question, and one that has been asked many times over the years.

Data Warehouse 52

Data Warehouse Data Integration Management Data Lake 52

Smart Data Collective

MAY 31, 2022

Data activation is a new and exciting way that businesses can think of their data. It’s more than just data that provides the information necessary to make wise, data-driven decisions. It’s more than just allowing access to data warehouses that were becoming dangerously close to data silos.

Data Warehouse 131

Data Warehouse Big Data Data-driven Technology 131

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 93

Analytics IT Data Lake Visualization 93

Data Virtualization

JULY 8, 2020

In my last post, I covered some of the latest best practices for enhancing data management capabilities in the cloud. Despite the increasing popularity of cloud services, enterprises continue to struggle with creating and implementing a comprehensive cloud strategy that.

Data Integration 52

Data Integration Strategy Enterprise Management 52

erwin

SEPTEMBER 26, 2019

The benefits of Data Vault automation from the more abstract – like improving data integrity – to the tangible – such as clearly identifiable savings in cost and time. So Seriously … You Should Automate Your Data Vault. By Danny Sandwell.

Data Warehouse 108

Data Warehouse Cost-Benefit Data Integration Modeling 108

DataKitchen

JANUARY 19, 2022

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers. Stronger Together.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0

Data Lake 109

Data Lake Data Warehouse Visualization Snapshot 109

Ontotext

APRIL 10, 2024

Knowledge graphs and semantic metadata Knowledge graphs (KGs) are the key to: Advanced Data Architecture & Models like Data Fabric, Data Mesh Unified Data Access Semantic Data Integration These fundamental capabilities of KGs enable them to bridge the chasm between information and knowledge in the DIKW pyramid.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

AWS Big Data

NOVEMBER 10, 2023

This integration expands the possibilities for AWS analytics and machine learning (ML) solutions, making the data warehouse accessible to a broader range of applications. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

Data Processing 89

Data Processing Data Lake Data Warehouse Optimization 89

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

IBM Big Data Hub

OCTOBER 30, 2023

AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics. Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market.

Insurance 85

Insurance Data Warehouse Data-driven Unstructured Data 85

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 94

Data Warehouse Snapshot Data Processing Management 94

AWS Big Data

JUNE 28, 2023

Another example of AWS’s investment in zero-ETL is providing the ability to query a variety of data sources without having to worry about data movement. Data analysts and data engineers can use familiar SQL commands to join data across several data sources for quick analysis, and store the results in Amazon S3 for subsequent use.

Analytics 66

Analytics Data Warehouse Data Lake Data-driven 66

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Data Virtualization

APRIL 11, 2024

Traditional data management approaches just won’t cut it, as they rely on physically replicating data from multiple systems into. The post Modern Data Solutions for the Supply Chain appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 52

Data Integration Management IT Data Warehouse 52

Smart Data Collective

APRIL 15, 2021

Set Up Data Integration. Data warehouses, a database that keeps the information in a processed and defined format, cannot connect directly to information sources, so data integration tools must process the raw data ahead of time to allow it to be usable.

Business Intelligence 96

Business Intelligence Analytics Statistics Data Warehouse 96

Data Virtualization

NOVEMBER 11, 2021

In the last few years, data virtualization technology has experienced tremendous growth, emerging as a key component for enabling modern data architectures such as the logical data warehouse, data fabric, and data mesh. Gartner recently named it “a must-have data.

Data Warehouse 52

Data Warehouse Data Architecture Technology IT 52

AWS Big Data

APRIL 3, 2024

Manage your Iceberg table with AWS Glue You can use AWS Glue to ingest, catalog, transform, and manage the data on Amazon Simple Storage Service (Amazon S3). With AWS Glue, you can discover and connect to more than 70 diverse data sources and manage your data in a centralized data catalog. Nidhi Gupta is a Sr.

Data Lake 92

Data Lake Snapshot Metadata Data Architecture 92

Smart Data Collective

JULY 20, 2021

Top Big Data CRM Integration Tools in 2021: #1 MuleSoft: Mulesoft is a data integration platform owned by Salesforce to accelerate digital customer transformations. This tool is designed to connect various data sources, enterprise applications and perform analytics and ETL processes.

Sales 140

Sales Big Data Marketing Software 140

CIO Business Intelligence

MARCH 16, 2022

The same goes for the adoption of data warehouse and business intelligence. The telecom sector prepares the data warehouse and business intelligence use cases even before they go live with their first customer. With regard to analytics in general, sadly, many organisations fail in their efforts to become data-driven.

Technology 115

Technology Digital Transformation Business Intelligence Data Warehouse 115

Data Virtualization

MARCH 7, 2024

One thing is clear; if data-centric organizations want to succeed in. The post Data Management Predictions for 2024: Five Trends appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Management 59

Management Data Integration Strategy Data Lake 59

FineReport

AUGUST 14, 2020

It is composed of three functional parts: the underlying data, data analysis, and data presentation. The underlying data is in charge of data management, covering data collection, ETL, building a data warehouse, etc. You can design, generate, and manage reports in this part.

Reporting 98

Reporting Informatics OLAP Data Warehouse 98

Ontotext

AUGUST 22, 2023

Worse, and according to Gartner, upward of 80% of enterprise data today is unstructured which further exacerbates the loss of knowledge, insights, and the wisdom needed to make effective business choices. As a result, organizations are looking for fresh data integration approaches to challenge the mindset with which we created them.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52