David Menninger's Analyst Perspectives

MARCH 30, 2020

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

Data Architecture 244

Data Architecture Unstructured Data Data Lake Data Governance 244

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. A modern ILM approach helps CIOs and their teams align processes to business objectives and regulatory requirements.

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Unstructured Data Data Lake Business Objectives Metadata 52

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Data Warehouse Cost-Benefit Unstructured Data Data Architecture 57

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

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Metadata Data Quality Data-driven Data Governance 52

Sisense

OCTOBER 6, 2020

These programs and systems are great at generating basic visualizations like graphs and charts from static data. The challenge comes when the data becomes huge and fast-changing. Why is quantitative data important? Qualitative data benefits: Unlocking understanding. Qualitative data can go where quantitative data can’t.

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Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

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Data Lake Metadata Optimization Statistics 109

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

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AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

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Data Lake Analytics Snapshot Optimization 84

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

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Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

JUNE 29, 2022

If you’re used to using SQL Server Analysis Services for business intelligence, Analysis Services offers that enterprise-grade analytics engine as a cloud service that you can also connect to Power BI. Azure Data Explorer. Azure Data Lake Analytics. Microsoft. Azure Analysis Services.

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Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

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Data Lake Data Warehouse Unstructured Data Business Intelligence 140

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

BizAcuity

MAY 10, 2022

2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. An efficient big data management and storage solution that AWS quickly took advantage of. They now have a disruptive data management solution to offer to its client base.

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Data-driven IoT Unstructured Data Data Lake 52

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. Today transactional data is the largest segment, which includes streaming and data flows.

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Data-driven Data Lake Data Warehouse Cost-Benefit 98

Sisense

MAY 28, 2019

Every decade, like clockwork, the Business Intelligence (BI) industry welcomes the next generation of BI platform providers. 2019 can best be described as an era of modern cloud data analytics. Two orthogonal approaches to data analytics have developed in this decade of BI: 1. The truth always rises to the surface.

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Data Analytics Data Lake Analytics Unstructured Data 89

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Using Alation, ARC automated the data curation and cataloging process. “So

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Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

FEBRUARY 21, 2023

It is a data modeling methodology designed for large-scale data warehouse platforms. What is a data vault? The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Dig into AI.

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Modeling Big Data IoT Data Warehouse 84

Cloudera

MAY 16, 2018

This example combines three types of unrelated data: Legal entity data: Two companies with completely unrelated business lines (coffee and waste management) merged together; Unstructured data: Fraudulent promotion campaigns took place through press releases and a fake stock-picking robot.

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Data Lake Risk Visualization Unstructured Data 41

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

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Data Quality Testing Data Warehouse Unstructured Data 73

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

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Data Architecture Data Lake Machine Learning Data Governance 66

AWS Big Data

JULY 28, 2023

Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools. Change the settings for existing Data Catalog resources.

Data Lake 64

Data Lake Data Governance Data Warehouse Modeling 64

Jet Global

NOVEMBER 21, 2023

Continued global digitalization is creating huge quantities of data for modern organizations. To have any hope of generating value from growing data sets, enterprise organizations must turn to the latest technology. Since then, technology has improved in leaps and bounds and data management has become more complicated.

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Data Lake Data Warehouse Reporting Enterprise 52