AWS Big Data

JUNE 21, 2023

A key pillar of AWS’s modern data strategy is the use of purpose-built data stores for specific use cases to achieve performance, cost, and scale. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 83

Data Warehouse Data Lake OLAP Cost-Benefit 83

CIO Business Intelligence

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

Machine Learning 132

Machine Learning Cost-Benefit Data-driven Strategy 132

CIO Business Intelligence

MAY 16, 2022

From the factory floor to online commerce sites and containers shuttling goods across the global supply chain, the proliferation of data collected at the edge is creating opportunities for real-time insights that elevate decision-making. The concept of the edge is not new, but its role in driving data-first business is just now emerging.

IoT 81

IoT Data Warehouse Internet of Things Machine Learning 81

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

AWS Big Data

FEBRUARY 27, 2024

Four-layered data lake and data warehouse architecture – The architecture comprises four layers, including the analytical layer, which houses purpose-built facts and dimension datasets that are hosted in Amazon Redshift. This enables data-driven decision-making across the organization.

Data-driven 98

Data-driven Data Lake Data Quality Data Governance 98

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The offensive side? The company’s Findability.ai

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

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. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 99

Data Governance Unstructured Data Metadata Data Lake 99

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

AWS Big Data

NOVEMBER 8, 2023

In today’s data-driven landscape, the quality of data is the foundation upon which the success of organizations and innovations stands. High-quality data is not just about accuracy; it’s also about timeliness. Reserve your seat now! Reserve your seat now!

Data-driven 92

Data-driven Data Lake Machine Learning Cost-Benefit 92

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

AWS Big Data

NOVEMBER 13, 2023

He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future. KEY003 | Swami Sivasubramanian (Vice President, Data and AI at AWS) | Nov.

Analytics 113

Analytics Data Lake Data Warehouse Data-driven 113

Sisense

JANUARY 1, 2020

5 Advantages of Using a Redshift Data Warehouse. Whatever business you’re in, your company is becoming a data company. That means you need to put all that data somewhere. Chances are it’s in a data warehouse, and even better money says it’s an AWS data warehouse. Read about how Sisense BloX 2.0

Analytics 98

Analytics Digital Transformation Data Warehouse Dashboards 98

AWS Big Data

MARCH 18, 2024

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

Data Warehouse 85

Data Warehouse Visualization Snapshot Data-driven 85

Cloudera

SEPTEMBER 2, 2020

Recently, Cloudera announced the release of Cloudera CDP Private Cloud, delivering the final component of our hybrid cloud strategy. Additionally, lines of business (LOBs) are able to gain access to a shared data lake that is secured and governed by the use of Cloudera Shared Data Experience (SDX). in an on-premise environment.

Cost-Benefit 66

Cost-Benefit Data Warehouse Data Lake Machine Learning 66

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. Additionally, the task of maintaining and managing files in the data lake can be tedious and sometimes complex. Dimension-based models have been used extensively to build data warehouses.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. Let’s talk about AI and machine learning (ML). AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

AWS Big Data

JULY 13, 2023

This allows for transparency, speed to action, and collaboration across the group while enabling the platform team to evangelize the use of data: Altron engaged with AWS to seek advice on their data strategy and cloud modernization to bring their vision to fruition.

Optimization 92

Optimization B2B Data Quality Sales 92

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 122

Analytics Data Science Statistics Unstructured Data 122

AWS Big Data

JANUARY 31, 2023

Amazon Redshift is a fully-managed, petabyte-scale data warehouse service in the AWS Cloud. The data sharing feature allows data owners to group databases, tables, and views in an Amazon Redshift cluster and share it with other Amazon Redshift clusters within or across AWS accounts. He helps customers become data-driven.

Data Lake 84

Data Lake Data Governance Data Architecture Machine Learning 84

Peter James Thomas

MAY 3, 2019

Data Architecture / Infrastructure. When I first started focussing on the data arena, Data Warehouses were state of the art. More recently Big Data architectures, including things like Data Lakes , have appeared and – at least in some cases – begun to add significant value. Data Strategy.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

AWS Big Data

JUNE 23, 2023

In this post, we explain how Imperva’s solution enables users across the organization to explore, visualize, and analyze data using Amazon Redshift Serverless , Amazon Athena , and QuickSight. Challenges and needs A modern data strategy gives you a comprehensive plan to manage, access, analyze, and act on data.

Data Lake 71

Data Lake Cost-Benefit Dashboards Data Warehouse 71

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Machine Learning Workspace exists . A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. The Data Scientist.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution.

Sales 52

Sales Data Warehouse Visualization Testing 52

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. Several factors are driving the adoption of knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

APRIL 6, 2022

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. Thinking about that intelligence as having millions of loosely connected decision points at the edge requires a different strategy, and you can’t micromanage it.

Data Strategy 52

Data Strategy Strategy Internet of Things Data Warehouse 52

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. To understand how the ODP framework met the company’s disaster recovery (DR) design criterion, we first need to understand the DR architecture strategy at a high level.

Data Lake 94

Data Lake Data Processing Metadata Snapshot 94

Sisense

MAY 28, 2020

As enterprises demand data infrastructures that can meet this growth in real-time data — and ultimately assist with their product differentiation strategy — the pressure put on product teams is huge. Product teams are already having to manage the growing complexities that come with modern data environments.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 86

Machine Learning Metrics Management Big Data 86

AWS Big Data

FEBRUARY 1, 2023

This post shows you how we migrated to a serverless data lake built on AWS that consumes data automatically from multiple sources and different formats. Furthermore, it created further opportunities for our data scientists and engineers to use AI and machine learning (ML) services to continuously feed and analyze data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

OCTOBER 4, 2023

Artificial intelligence (AI) is now at the forefront of how enterprises work with data to help reinvent operations, improve customer experiences, and maintain a competitive advantage. It’s no longer a nice-to-have, but an integral part of a successful data strategy. How does an open data lakehouse architecture support AI?

Data Lake 83

Data Lake Metadata Cost-Benefit Data Warehouse 83

Cloudera

NOVEMBER 25, 2020

How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic. Access to valuable data should not be hindered by the technology.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

CIO Business Intelligence

MAY 24, 2022

Australian research and advisory firm Adapt identifies an organisation’s ability to execute a data-driven strategy as one of 12 core competencies , identified from 30,000 conversations spanning three years with leading IT and businesses. This is the first post in a series of three on data-driven organisations.

Data-driven 81

Data-driven Data Lake Data Warehouse Cost-Benefit 81