Data Virtualization

JUNE 16, 2022

Reading Time: 6 minutes Data Governance as a concept and practice has been around for as long as data management has been around. It, however is gaining prominence and interest in recent years due to the increasing volume of data that needs to be.

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AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

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Metadata Snapshot Data Lake Metrics 126

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Data silos are a perennial data management problem for enterprises, with almost three-quarters (73%) of participants in ISG Research’s Data Governance Benchmark Research citing disparate data sources and systems as a data governance challenge.

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David Menninger's Analyst Perspectives

JUNE 12, 2019

Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.

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AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

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CIO Business Intelligence

AUGUST 9, 2024

The original proof of concept was to have one data repository ingesting data from 11 sources, including flat files and data stored via APIs on premises and in the cloud, Pruitt says. There are a lot of variables that determine what should go into the data lake and what will probably stay on premise,” Pruitt says.

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CIO Business Intelligence

APRIL 1, 2024

GenAI requires high-quality data. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key.

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BI-Survey

AUGUST 21, 2020

The primary modernization approach is data warehouse/ETL automation, which helps promote broad usage of the data warehouse but can only partially improve efficiency in data management processes. However, an automation approach alone is of limited usefulness when data management processes are inefficient.

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Cloudera

MAY 28, 2024

This form of architecture can handle data in all forms—structured, semi-structured, unstructured—blending capabilities from data warehouses and data lakes into data lakehouses.

Data Architecture 94

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AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

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AWS Big Data

DECEMBER 15, 2023

Even after identification, it’s cumbersome to implement redaction, masking, or encryption of sensitive data at scale. In this post, we provide an automated solution to detect PII data in Amazon Redshift using AWS Glue. For our solution, we use Amazon Redshift to store the data.

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CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

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Data Architecture Management Consulting Internet of Things 98

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 Data Warehouse 105

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. For more information on AWS Glue, visit AWS Glue.

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CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

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Analytics Key Performance Indicator Data Warehouse Data-driven 115

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. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 118

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AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. Kamen Sharlandjiev is a Sr.

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Data Processing Visualization Data Lake Data Processing 113

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

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Management Metadata Data Architecture Data Lake 79

CIO Business Intelligence

MAY 24, 2022

However, this concept has evolved in line with the increasing demands of mature and sophisticated data-driven organisations, and with the increased use and sophistication of cloud computing services. store and process the data, typically in a data warehouse, where the data is modelled and schema applied. Oil and Gas.

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AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 94

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Cloudera

MARCH 5, 2024

With built-in features like time travel, schema evolution, and streamlined data discovery, Iceberg empowers data teams to enhance data lake management while upholding data integrity. Available for cloud and now also for the data center. And that’s also what makes Cloudera so unique.

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Snapshot Data Lake Enterprise Data Governance 92

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities. option("header",True).schema(schema).load("s3://"+

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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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

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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.

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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.

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CIO Business Intelligence

AUGUST 2, 2023

With the first two layers, the business is the driver with IT in a support role, but with the data governance and architecture layer, IT and the business are side by side, working through complex decisions about governance and architecture together. These aren’t typically business discussions; it’s largely IT.

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Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

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David Menninger's Analyst Perspectives

OCTOBER 7, 2021

In this post, I don’t want to debate the meanings and origins of different terms; rather, I’d like to highlight a technology weapon that you should have in your data management arsenal. We currently refer to this technology as data virtualization.

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Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. A set of QuickSight dashboards to be consumed via browser and mobile.

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Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

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Data Governance Machine Learning Metadata Data Science 84

IBM Big Data Hub

OCTOBER 12, 2023

Accounting for the complexities of the AI lifecycle Unfortunately, typical data storage and data governance tools fall short in the AI arena when it comes to helping an organization perform the tasks that underline efficient and responsible AI lifecycle management. And that makes sense.

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Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

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Data Warehouse ROI Data Integration Internet of Things 98

IBM Big Data Hub

JANUARY 5, 2023

Next generation of big data platforms and long running batch jobs operated by a central team of data engineers have often led to data lake swamps. Meaning, data architecture is a foundational element of your business strategy for higher data quality.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

AWS Big Data

JULY 19, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. Conclusion In this post, we showed how to use AWS Glue and the new connector for ingesting data from Google Cloud Storage to Amazon S3.

Big Data 98

Big Data Software Consulting Unstructured Data 98

BI-Survey

APRIL 27, 2023

Lessons about data modeling, modernization, and automation include the following: Focus on fundamentals Companies place the highest priority on data quality, ease of use, analytics performance, and data governance. The lakehouse, data fabric, and data mesh have 8-12% usage each.

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Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

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Metadata Data Architecture Machine Learning Cost-Benefit 97