AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 101

Data Warehouse Data Processing Data Lake Management 101

ScienceSoft

NOVEMBER 28, 2019

Learn what a cloud data warehouse is and what distinguishes it from traditional DWHs. Explore what market leaders offer and check how-to-mitigate-the-risk recommendations.

Data Warehouse 76

Data Warehouse Risk Marketing IT 76

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. He works with customers and engineering teams to build new features that enable data engineers and data analysts to more easily load data, manage data warehouse resources, and query their data.

Data Warehouse 94

Data Warehouse Management Snapshot Data Lake 94

CIO Business Intelligence

JULY 28, 2023

This approach allows enterprises to streamline processes, gather data for specific purposes, get better insights from data in a secure environment, and efficiently share it. 1 A clear picture of where data lives and how it moves enables enterprises to consistently protect this data and its privacy.

Risk 98

Risk Management Data mining Cost-Benefit 98

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. The tools to transform your business are here.

Data Analytics 88

Data Analytics Analytics Data Lake Data Quality 88

Cloudera

APRIL 9, 2021

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. ETL jobs and staging of data often often require large amounts of resources.

Data Warehouse 58

Data Warehouse Statistics Cost-Benefit Data-driven 58

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. They prevent you from drowning in data. The data warehouse.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Visualization 270

BI-Survey

NOVEMBER 19, 2018

S mall companies are more likely than large or mid-sized companies to implement BI tools and data warehouses in the cloud. This makes sense because many small companies may not have a legacy BI/data warehouse environment and internal data center or the IT staff that can build something in-house.

Data Warehouse 66

Data Warehouse Reporting Risk Optimization 66

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. The Stripe Data Pipeline is powered by the data sharing capability of Amazon Redshift.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

AWS Big Data

FEBRUARY 1, 2024

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. This will be your OLTP data store for transactional data. version cluster. version cluster.

Data Warehouse 133

Data Warehouse Dashboards Risk Management Risk 133

AWS Big Data

JUNE 29, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

Data Warehouse 66

Data Warehouse Dashboards Testing Visualization 66

AWS Big Data

APRIL 17, 2024

The AaaS model accelerates data-driven decision-making through advanced analytics, enabling organizations to swiftly adapt to changing market trends and make informed strategic choices. times better price-performance than other cloud data warehouses. Data processing jobs enrich the data in Amazon Redshift.

Data Warehouse 115

Data Warehouse Analytics Cost-Benefit Data Processing 115

AWS Big Data

JULY 24, 2024

ActionIQ is a leading composable customer data (CDP) platform designed for enterprise brands to grow faster and deliver meaningful experiences for their customers. This post will demonstrate how ActionIQ built a connector for Amazon Redshift to tap directly into your data warehouse and deliver a secure, zero-copy CDP.

Data Warehouse 114

Data Warehouse Cost-Benefit Marketing Testing 114

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 70

Risk Modeling Management Metadata 70

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

erwin

SEPTEMBER 3, 2020

You can collect complete application ecosystem information; objectively identify connections/interfaces between applications, using data; provide accurate compliance assessments; and quickly identify security risks and other issues. You can better manage risk because of real-time data coming into the EA space.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. Key areas of concern are: .

Data Warehouse 104

Data Warehouse Reporting Risk Cost-Benefit 104

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 59

Data Warehouse Unstructured Data Analytics Visualization 59

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 116

Data Warehouse Analytics Data Lake Machine Learning 116

CIO Business Intelligence

OCTOBER 19, 2022

“So, at Zebra, we created a hub-and-spoke model, where the hub is data engineering and the spokes are machine learning experts embedded in the business functions. We kept the data warehouse but augmented it with a cloud-based enterprise data lake and ML platform. What about risk? What about security?

IT 124

IT Data Warehouse Digital Transformation Risk 124

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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. So being prepared means you can minimize your risk exposure and the damage to your reputation.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

Laminar Security

JULY 19, 2023

To effectively protect sensitive data in the cloud, cyber security personnel must ensure comprehensive coverage across all their environments; wherever data travels, including cloud service providers (CSPs), data warehouses, and software-as-a-service (SaaS) applications.

Data Warehouse 91

Data Warehouse Data-driven Data Governance Measurement 91

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets.

Data Warehouse 94

Data Warehouse Data Lake IT Analytics 94

erwin

FEBRUARY 13, 2020

Therefore, most enterprises have encountered difficulty trying to master data governance and metadata management, but they need a solid data infrastructure on which to build their applications and initiatives. Data Governance Attitudes Are Shifting. Metadata Management Takes Time.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

AWS Big Data

SEPTEMBER 22, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Merge operation reduces this risk by ensuring that all operations are performed together in a single transaction.

Data Warehouse 120

Data Warehouse OLAP Risk Online Analytical Processing 120

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Data-driven 150

CIO Business Intelligence

NOVEMBER 7, 2024

If we understand the data better and derive better insights, it enables us to offer better products and services at greater speed. We have modernized most of our data warehouses, we have put in new tools and capabilities, and that’s great, because now we’re at this next inflection point of technology with gen AI.

Insurance 120

Insurance Experimentation Testing Technology 120

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

IBM Big Data Hub

MAY 9, 2023

With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. Savings may vary depending on configurations, workloads and vendors.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 102

Data Warehouse KPI Optimization Cost-Benefit 102

Jet Global

JANUARY 5, 2021

Many AX customers have invested heavily in data warehouse solutions or in robust Power BI implementations that produce considerably more powerful reports and dashboards. Business leaders should be clear about the risks before going ahead with a full-stack Power BI implementation. Now More Than Ever, Reporting Is Critical.

Reporting 98

Reporting Data Warehouse Finance Dashboards 98

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Cloudera

MAY 28, 2024

Modern data architectures deliver key functionality in terms of flexibility and scalability of data management. 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 88

Data Architecture Data Lake Data Warehouse Cost-Benefit 88

Cloudera

MAY 10, 2021

The introduction of CDP Public Cloud has dramatically reduced the time in which you can be up and running with Cloudera’s latest technologies, be it with containerised Data Warehouse , Machine Learning , Operational Database or Data Engineering experiences or the multi-purpose VM-based Data Hub style of deployment.

Data Warehouse 104

Data Warehouse Machine Learning Consulting Risk 104

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88