David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 311

Management Data Warehouse Data Quality Data Integration 311

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 59

Data Warehouse Dashboards Testing Visualization 59

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architect vs. data engineer The data architect and data engineer roles are closely related.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

Smart Data Collective

MAY 31, 2022

Big data technology is having a huge impact on the state of modern business. The technology surrounding big data has evolved significantly in recent years, which means that smart businesses will have to take steps to keep up with it. What is Data Activation? It Started Reverse ETL.

Data Warehouse 133

Data Warehouse Big Data Data-driven Technology 133

CDW Research Hub

MARCH 22, 2019

Siloed data-storage systems were preventing a large and fast-growing franchisor and operator of fitness centers from gaining important insights to drive further business growth. Access to and visibility of critical customer data was unleashed with the help of Sirius. empowering franchisees to use data for business decision-making, and.

Data Warehouse 66

Data Warehouse Prescriptive Analytics Statistics Big Data 66

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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

Smart Data Collective

JUNE 7, 2019

With today’s technology, there’s an increasing demand for stream processing. Data, for instance, has to be processed fast so that the companies can keep up to the changing business and market conditions in real time. Read this article as we’ll tackle what big data and stream processing are. What is Big Data?

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 130

Analytics Data Science Statistics Unstructured Data 130

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 95

Analytics IT Data Lake Visualization 95

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. Business intelligence analyst job requirements BI analysts typically handle analysis and data modeling design using data collected in a centralized data warehouse or multiple databases throughout the organization.

Business Intelligence 125

Business Intelligence Data-driven Statistics Data Warehouse 125

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.

Data Warehouse 121

Data Warehouse Dashboards Risk Management Risk 121

Cloudera

FEBRUARY 7, 2019

Who knew that in that search, the company would become the first organization to globally run SAS Viya, a cloud-optimized software, with HDP on GCP to enable modern analytics use cases powered by SAS analytics tools. Implementing a Modern Data Architecture. Reducing Analytic Time to Value by More Than 90 Percent.

Big Data 63

Big Data Data Analytics Analytics Data Architecture 63

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. This may lead to misleading evaluations about the technology or concept being tested.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

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

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

IBM Big Data Hub

AUGUST 28, 2023

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. For more than 10 years, the publisher has used IBM Cognos Analytics to wrangle its internal and external operational reporting needs. This contributed to the need for more analytics by our users.

Publishing 54

Publishing Analytics Business Intelligence Operational Reporting 54

Smart Data Collective

APRIL 15, 2021

Data warehouses, a database that keeps the information in a processed and defined format, cannot connect directly to information sources, so data integration tools must process the raw data ahead of time to allow it to be usable. The technology continues to evolve, including cloud-based and mobile platforms.

Business Intelligence 97

Business Intelligence Analytics Statistics Data Warehouse 97

AWS Big Data

MAY 17, 2023

Credit: Phil Goldstein Jerry Wang, Peloton’s Director of Data Engineering (left), and Evy Kho, Peloton’s Manager of Subscription Analytics, discuss how the company has benefited from using Amazon Redshift. 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

bridgei2i

APRIL 21, 2021

He elaborates how ERP technology was adopted in the early 70s based on the computational power available at that time. The 2000s saw data warehouses being created and used as business intelligence picked up. In the current landscape, supply chains are an outcome of big data, machine learning and artificial technologies.

Forecasting 98

Forecasting Data Warehouse Manufacturing Machine Learning 98

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 100

Data Lake Sales Data Warehouse Snapshot 100

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. Real-world Business Solutions The real value of any technology is measured by its impact on real-world problems.

Insurance 86

Insurance Data Warehouse Data-driven Unstructured Data 86

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Jen Stirrup

MAY 3, 2020

Azure Synapse is an Azure-based cloud analytics service that provides insights on all data across data warehouses and big data analytics systems. It combines familiar SQL technologies such as data warehousing with Spark technologies used in big data analytics.

Big Data 56

Big Data Data Warehouse Machine Learning Business Intelligence 56

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

Smart Data Collective

NOVEMBER 18, 2020

The Bureau of Labor Statistics estimates that the number of data scientists will increase from 32,700 to 37,700 between 2019 and 2029. Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. Where to Use Data Mining? Practical experience.

Data mining 143

Data mining Data Science Informatics Statistics 143

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

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Azure Data Lakes are complicated.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Jen Stirrup

MAY 5, 2020

How can you differentiate the different opportunities to store your data in Azure? Now, it may not sound that interesting, but it’s crucial; if you don’t have your data, then you don’t have your business. So how do you choose which data source is right for your needs?

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Third-party APIs – These provide analytics and survey data related to ecommerce websites.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

AWS Big Data

OCTOBER 20, 2023

One of the data sources you can now quickly integrate with is Azure Blob Storage, a managed service for storing both unstructured data and structured data, and Azure Data Lake Storage, a data lake for analytics workloads. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Data Lake 82

Data Lake Big Data Consulting Data Warehouse 82

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 105

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 105