AWS Big Data

NOVEMBER 29, 2023

The Eightfold Talent Intelligence Platform powered by Amazon Redshift and Amazon QuickSight provides a full-fledged analytics platform for Eightfold’s customers. It delivers analytics and enhanced insights about the customer’s Talent Acquisition, Talent Management pipelines, and much more.

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Analytics Vidhya

SEPTEMBER 18, 2022

Introduction Apache SQOOP is a tool designed to aid in the large-scale export and import of data into HDFS from structured data repositories. Relational databases, enterprise data warehouses, and NoSQL systems are all examples of data storage. It is a data migration tool […].

Data Warehouse 271

Data Warehouse Structured Data Data Science Publishing 271

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.

Data Warehouse 88

Data Warehouse Analytics Metrics Snapshot 88

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

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

MAY 2, 2024

Amazon Redshift recently announced integration with Visual Studio Code (), an action that transforms the way data practitioners engage with Amazon Redshift and reshapes your interactions and practices in data management. Set up a Amazon Redshift or Amazon Redshift serverless data warehouse. Virginia)).

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Visualization Data Warehouse Data-driven Management 88

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 319

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Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

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Jet Global

JANUARY 30, 2024

Prepare to ditch the one-size-fits-all mentality and design an ESPP that’s not just a perk, but a strategic weapon driving engagement and retention. Knowing what you want to achieve with your plan will enable you to craft the best plan design. Design your ESPP around its features. Seamlessly align with company goals.

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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.

Business Analytics 245

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Cloudera

FEBRUARY 9, 2021

This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability. In this way, the analytic applications are able to turn the latest data into instant business insights. Low Maintenance.

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Data Warehouse Cost-Benefit Metadata Management 67

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

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 134

Analytics Data Science Unstructured Data Data mining 134

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Any hardware failures are automatically replaced.

Analytics 92

Analytics Data Warehouse Testing Dashboards 92

Cloudera

SEPTEMBER 24, 2020

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

Data Warehouse 68

Data Warehouse Metadata Interactive Dashboards 68

AWS Big Data

NOVEMBER 13, 2023

Join the AWS Analytics team at AWS re:Invent this year, where new ideas and exciting innovations come together. For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. A shapeshifting guardian and protector of data like Data Lynx?

Analytics 109

Analytics Data Lake Data Warehouse Data-driven 109

Jet Global

APRIL 30, 2024

The ever-growing threat landscape of hackers, cyberattacks, and data breaches makes data security a top priority, especially when integrating analytics capabilities directly into customer-facing applications. While these platforms secure dashboards and reports, a hidden vulnerability lies within the data connector.

Analytics 52

Analytics Data Processing Dashboards Reporting 52

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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Data Warehouse Sales Visualization Data Processing 76

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

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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AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 87

Data Analytics Analytics Data Warehouse Data Lake 87

DataKitchen

AUGUST 19, 2021

For those embarking on the data mesh journey, it may be helpful to discuss a real-world example and the lessons learned from an actual data mesh implementation. DataKitchen has extensive experience using the data mesh design pattern with pharmaceutical company data. . Pharma Data Requirements.

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Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data at petabyte scale, using standard SQL and your existing business intelligence (BI) tools. Their cluster size of the provisioned data warehouse didn’t change.

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Data Warehouse Analytics Testing Cost-Benefit 59

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 architects are frequently part of a data science team and tasked with leading data system projects.

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Data Architecture Data Warehouse Statistics Visualization 131

Smarten

DECEMBER 19, 2023

The Right Augmented Analytics Supports Your Team and Your Business! When you embark on an analytics deployment, you want to be sure that you get what you need. When considering a self-serve augmented analytics solution, there are numerous factors to include in your assessment.’ And there is good reason for that.

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Analytics Machine Learning Sales Data Warehouse 62

Jet Global

JANUARY 20, 2021

Data, Data, and More Data. Add web analytics, digital marketing automation, and social media to the mix, and the volume of data grows even further. Pile on external data from suppliers and external service providers, and it begins to appear unmanageable. JSMITH01”). Human error introduces problems as well.

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Data Analytics Management Analytics Data Warehouse 95

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

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Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

DECEMBER 19, 2023

Sun King designs, distributes, installs, and finances solar home energy products for people currently living without reliable energy access. Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale.

Data Analytics 62

Data Analytics Analytics Data Warehouse Data-driven 62

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 127

Analytics Data Science Statistics Unstructured Data 127

AWS Big Data

MARCH 21, 2024

In this post, we provide step-by-step guidance on how to get started with near real-time operational analytics using this feature. This post is a continuation of the zero-ETL series that started with Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift.

Data Warehouse 84

Data Warehouse Metrics Optimization Statistics 84

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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.

Measurement 79

Measurement Dashboards Data Warehouse Analytics 79

Jet Global

FEBRUARY 21, 2024

Pressure for on-demand data insights is increasing as potential buyers look for intuitive, but deep analytics functionality to help navigate their business through these uncertain economic times. According to insightsoftware and Hanover Research’s 2024 Embedded Analytics Report , customizable dashboards are in demand.

Analytics 52

Analytics Dashboards Predictive Analytics Software 52

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 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

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. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). So let’s dive in!

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Data Warehouse OLAP Statistics Cost-Benefit 78

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Jet Global

APRIL 18, 2024

Companies that offer products to their customers demand analytics, all while juggling multiple priorities. Customers expect rapid value from your product (time-to-value), unwavering security of their data, and access to advanced analytics capabilities. Embedded analytics offers a strategic solution to this challenge.

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Marketing Analytics Data Processing Cost-Benefit 52