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.

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Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

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AWS Big Data

APRIL 10, 2024

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics.

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Data Warehouse Analytics Metrics Snapshot 92

Cloudera

DECEMBER 20, 2022

In this respect, several studies project that a proper use of advanced analytics implies savings of between 5% and 7.5%. The impact of the use of different analytical techniques in this field increases the profitability of these companies by 5% to 10%, at the same time increasing the brand value by increasing customer satisfaction.

Optimization 81

Optimization Data Analytics Analytics Cost-Benefit 81

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

DataKitchen

AUGUST 27, 2021

Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. This analytics function is so crucial to product success that the data team often reports directly into sales and marketing. As figure 2 summarizes, the data team ingests data from hundreds of internal and third-party sources.

Analytics 246

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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.

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DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. In business analytics, fire-fighting and stress are common. Analytics Hub and Spoke.

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Business Analytics Analytics Testing Dashboards 245

Analytics Vidhya

AUGUST 3, 2022

Introduction Regarding data analytics, getting insights from a data mart instead of a data warehouse or external data sources can save companies time and produce more targeted results. data marts is not new – they’ve been around for at least […]. The idea of ??data

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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.

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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.

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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.

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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.

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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.

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Analytics Data Science Unstructured Data Data mining 133

AWS Big Data

DECEMBER 5, 2023

This cut down significantly on analytical turnaround times. The CARTO Analytics Toolbox for Redshift is composed of a set of user-defined functions and procedures organized in a set of modules based on the functionality they offer. Kiran Kumar Tati is an Analytics Specialist Solutions Architect based out of Omaha, NE.

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Measurement Dashboards Data Warehouse Analytics 82

CIO Business Intelligence

MARCH 9, 2022

Organizations are increasingly trying to grow revenue by mining their data to quickly show insights and provide value. In the past, one option was to use open-source data analytics platforms to analyze data using on-premises infrastructure. Cloudera and Dell Technologies for More Data Insights.

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CIO Business Intelligence

SEPTEMBER 10, 2022

American Airlines, the world’s largest airline, is turning to data and analytics to minimize disruptions and streamline operations with the aim of giving travelers a smoother experience. We moved our major data platforms to the cloud and implemented data hubs for Customer and Operations,” Mohan says. Taking to the cloud.

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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.

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Analytics IT Data Lake Visualization 96

Sisense

MARCH 6, 2019

Every year there’s high anticipation to see what key message Gartner will present in the yearly Data & Analytics Summits. The crowd who attends these events are made mostly of analytics leaders in Enterprises. Analytics leaders can only get buy-in if people understand the story of the journey and its purpose.

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Data Analytics Analytics Experimentation Data-driven 75

DataKitchen

AUGUST 19, 2021

In figure 1 below, we see that the data requirements are quite different for each of three critical phases of a drug’s lifecycle: Table 1: Lifecycle phases of pharmaceutical product launch. Each distinct phase of the drug lifecycle requires a unique focus for analytics. Pharma Data Requirements. The new Recipes run, and BOOM!

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Data Warehouse Data Lake Manufacturing Testing 246

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.

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AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 112

Analytics IoT Data-driven Snapshot 112

Smarten

DECEMBER 3, 2023

Adopting Augmented Analytics: How to Get Started Gartner has predicted that, in the future ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’ What do you want to achieve by implementing an augmented analytics solution?

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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

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.

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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.

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IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

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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.

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Data Warehouse Dashboards Risk Management Risk 123

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. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses.

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Sisense

AUGUST 4, 2021

The Sisense Q2 2021 product release is packed with exciting innovations and enhancements that offer users a more extensible experience when it comes to analytics. Analytics adoption has stalled; only infused analytics can help. Sisense Explanations deepens your understanding of your data. Learn more. Learn more.

Dashboards 52

Dashboards Analytics Data Warehouse Forecasting 52

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

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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

Alation

FEBRUARY 13, 2020

Earlier this month in London, more than 1,600 data and analytics leaders and professionals gathered for the Gartner Data & Analytics Summit. From niche breakout sessions to the packed opening keynote—where “AI” was one of three leading trends along with “data driven” and “privacy”— AI was everywhere.

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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.

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Data Warehouse Cost-Benefit Sales Data-driven 111

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

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Optimization Marketing Analytics Data Warehouse 52

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. Iterations of the lakehouse.

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Data Lake Data Warehouse Machine Learning Cost-Benefit 98