Timo Elliott

MAY 27, 2022

First, data is by default, and by definition, a liability , because it costs money and has risks associated with it. To turn data into an asset , you actually have to do something with it and drive the business. And the best way to do that is to embed data, analytics, and decisions into business workflows.

Data Analytics 114

Data Analytics Analytics Recreation/Entertainment Data Lake 114

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 77

Data Warehouse Analytics Cost-Benefit Modeling 77

David Menninger's Analyst Perspectives

OCTOBER 5, 2021

Alteryx is a data analytics software company that offers data preparation and analytics tools to simplify and automate data wrangling, data cleaning and modeling processes, enabling line-of-business personnel to quickly access, manipulate, analyze and output data.

Analytics 274

Analytics Data Warehouse Software Modeling 274

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data Architecture 54

AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 91

Data Warehouse Analytics Metrics Snapshot 91

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. Typical tools for data science: SAS, Python, R. What is Data Analytics?

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Cloudera

DECEMBER 20, 2022

Try Cloudera DataFlow (CDF), Cloudera Data Warehouse (CDW), Cloudera Data Engineering (CDE), and Cloudera Machine Learning (CML) by signing up for a 60 day trial , or test drive CDP. If you are interested in chatting about how to manage the full data lifecycle with CDP, let your account team know or contact us directly.

Optimization 81

Optimization Data Analytics Analytics Cost-Benefit 81

David Menninger's Analyst Perspectives

NOVEMBER 30, 2021

TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes.

Analytics 160

Analytics Data Warehouse Business Intelligence Software 160

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g., Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

Andrew White

MARCH 22, 2021

Henry Cook scores his first “number 1” hit this year with this iteration of The Practical Logical Data Warehouse that was published in December 2020. “The logical data warehouse — a data consolidation and virtualization architecture of multiple analytic systems — is used by both user organizations and vendors.

Data Warehouse 52

Data Warehouse Analytics Data Analytics Interactive 52

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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 Risk 91

Dataiku

NOVEMBER 29, 2023

In the not-so-distant past, businesses heavily invested in self-service analytics and desktop applications for data preparation , striving to harness the power of their data and empower their teams.

Analytics 59

Analytics Data Warehouse Data Analytics 59

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. The organizational concepts behind data mesh are summarized as follows.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

David Menninger's Analyst Perspectives

MARCH 17, 2022

Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.

Business Intelligence 162

Business Intelligence Data Warehouse Data Quality Dashboards 162

Data Virtualization

AUGUST 19, 2021

“Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical.

Data Lake 98

Data Lake Data Warehouse Data Analytics Analytics 98

Data Virtualization

AUGUST 19, 2021

“Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical.

Data Lake 98

Data Lake Data Warehouse Data Analytics Analytics 98

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Overall data architecture and strategy. Use case priority and workload identifications.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 122

Data Warehouse Dashboards Risk Management Risk 122

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. The post How Will The Cloud Impact Data Warehousing Technologies?

Technology 130

Technology Data Warehouse Big Data Machine Learning 130

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 110

Data Warehouse Cost-Benefit Sales Data-driven 110

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 91

Data Warehouse Data-driven Machine Learning B2B 91

AWS Big Data

DECEMBER 5, 2023

We encourage you to explore Redshift Serverless with CARTO for analyzing spatial data and let us know your experience in the comments. She helps customers architect data analytics solutions at scale on AWS. Washim Nawaz is an Analytics Specialist Solutions Architect at AWS. Solutions Architect at Amazon Web Services.

Measurement 81

Measurement Dashboards Data Warehouse Analytics 81

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 97

Data Warehouse Testing Data Lake Data-driven 97

Sisense

MARCH 6, 2019

A big part of our Elastic Data Hub strategy comes from the belief that even the best data warehouses need rapid prototyping environments for BI professionals. At Sisense we’ve been preaching for BI prototyping and experimentation for quite a while now.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

Insurance 82

Insurance Data Warehouse Data-driven Unstructured Data 82

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The first diagram illustrates the architecture before using data sharing.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 94

Data Governance Unstructured Data Metadata Data Lake 94

Cloudera

FEBRUARY 7, 2019

This has become a core component of the fraud management framework for the business, and has helped solidify its role as the trusted keeper of sensitive data. Reducing Analytic Time to Value by More Than 90 Percent. ATB Financial is also the first to use SAS Viya to interface between SAS tools and HDP. Check out our customer stories.

Big Data 66

Big Data Data Analytics Analytics Data Architecture 66

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. In this way, the Cloud Data Warehouse Accelerator enables a seamless transition to Snowflake. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52