AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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. When data is stored in a modern, accessible repository, organizations gain newfound capabilities. Connect/Activate.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

CIO Business Intelligence

JULY 26, 2023

The only thing we have on premise, I believe, is a data server with a bunch of unstructured data on it for our legal team,” says Grady Ligon, who was named Re/Max’s first CIO in October 2022. The gen AI model will save agents time and create better listings. minutes from the moment the property is listed.

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

IBM Big Data Hub

MAY 19, 2023

According to the research, organizations are adopting cloud ERP models to identify the best alignment with their strategy, business development, workloads and security requirements. With high-speed file transfer, integrated services and cross-region offerings, IBM Cloud Object Storage allows you to leverage your data securely.

Unstructured Data 80

Unstructured Data Data Processing Manufacturing Data Lake 80

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

Data Lake 72

Data Lake Testing Interactive Unstructured Data 72

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. You can integrate different technologies or tools to build a solution.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

IBM Big Data Hub

FEBRUARY 2, 2023

Organizations looking to increase adoption of ML are turning to cloud data warehouses that support new, open data formats to catalog, ingest, and query unstructured data types. Additionally, some DBAs worry that moving to the cloud reduces the need for their expertise and skillset.

Data Warehouse 58

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 58

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.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Sisense

OCTOBER 6, 2020

These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.

Statistics 98

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.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

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.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Data Explorer. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale. This is where the tagging feature in Apache Iceberg comes in handy.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

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.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. 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. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. EC2 was a more evolved version of a Virtual Machine.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

CIO Business Intelligence

MAY 24, 2022

Today transactional data is the largest segment, which includes streaming and data flows. EXTRACTING VALUE FROM DATA. One of the biggest challenges presented by having massive volumes of disparate unstructured data is extracting useable information and insights. CLOUDERA DATA PLATFORM (CDP) IN ACTION.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

Sisense

MAY 28, 2019

Two orthogonal approaches to data analytics have developed in this decade of BI: 1. Operating “in-data” to enable the direct query of unstructured data lakes, providing a visualization layer on top of them. Then, and only then, can they operationalize their BI on top of the cloud data lake.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. In doing so, Bank of the West has modernized and centralized its Big Data platform in just one year.

Data Lake 73

Data Lake Cost-Benefit Digital Transformation Risk 73

AWS Big Data

FEBRUARY 21, 2023

Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Additionally, scalability of the dimensional model is complex and poses a high risk of data integrity issues. What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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? They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Cloudera

AUGUST 21, 2020

And next to those legacy ERP, HCM, SCM and CRM systems, that mysterious elephant in the room – that “Big Data” platform running in the data center that is driving much of the company’s analytics and BI – looks like a great potential candidate. . Vendors come and go. New priorities emerge.

Cost-Benefit 71

Cost-Benefit Big Data ROI Risk 71

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Cloudera

JUNE 4, 2018

That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data. Nguyen, Accenture & Mitch Gomulinski, Cloudera. How can they tackle this challenge?

Unstructured Data 45

Unstructured Data Metadata Big Data Enterprise 45

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. Market data: Coordinated trading among multiple parties.

Data Lake 41

Data Lake Risk Visualization Unstructured Data 41

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

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.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

AWS Big Data

JULY 28, 2023

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Lake 64

Data Lake Data Governance Data Warehouse Modeling 64

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Limited flexibility to use more complex hosting models (e.g.,

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

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.

Data Lake 52

Data Lake Data Warehouse Reporting Enterprise 52