AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. For more information, refer SQL models.

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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.

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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. Analytics Specialist based out of Northern Virginia, specialized in the design and implementation of analytics and data lake solutions.

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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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DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data. DataOps Success Story.

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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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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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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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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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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. Whether or not they begin with on-premises systems, such modernization efforts often involve the implementation of hybrid configurations.

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Smarten

DECEMBER 24, 2019

The Smarten team provided dedicated services and support to understand their functional requirements, and to design and implement a centralized data warehouse, ETL, and front-end object development. Download the Case Study.

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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.

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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.

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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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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.

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Jet Global

MAY 1, 2020

Recently released is a report by Gartner about all the things that can go wrong in your BI implementation. Aided by our teams’ experiences here at insightsoftware, we’ve summarized them into nine distinct threats to your BI implementation. The mechanical solution is to build a data warehouse. View Guide Now. We’re done.

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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. For a POC on Amazon Redshift, we recommend a three-phase process of discovery, implementation, and evaluation.

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CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

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Smarten

JANUARY 18, 2023

It is a highly process driven company and depends on data and its analysis for decision making and reporting at each level in the organization. From a Forest of Spreadsheets to Centralized Self-Service Analytics. Download the Case study.

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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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AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

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KDnuggets

AUGUST 17, 2022

In this practical modern data stack course, you will implement a dbt project on a data warehouse from scratch and with a lot of support along the way!

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Smarten

JANUARY 16, 2023

The Smarten team successfully implemented an augmented analytics solution that fulfilled all client requirements. The Smarten team helped build a data warehouse and consolidate it with NSE source data that was most of the times available in a different format. Download the Case study.

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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.

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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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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

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AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Implement data privacy policies. Implement data quality by data type and source.

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Smart Data Collective

APRIL 15, 2021

Business Intelligence uses methods and tools like machine learning to take massive, unstructured swaths of data and turn them into easy-to-use reports. But how exactly to implement BI into a company? You need to make sure that all departments are data-friendly and in sync with each other. Set Up Data Integration.

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AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

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AWS Big Data

APRIL 29, 2024

It can integrate with external tools for advanced analytics on these audit logs. Ranger Key Management Store (KMS) – Ranger KMS provides encryption and key management, extending Hadoop’s HDFS Transparent Data Encryption (TDE). This provides data security and orderly conduct of daily business operations.

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DataKitchen

AUGUST 3, 2021

DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . This post (1 of 5) is the beginning of a series that explores the benefits and challenges of implementing a data mesh and reviews lessons learned from a pharmaceutical industry data mesh example.

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CIO Business Intelligence

JULY 18, 2022

The organization operates a federated network, with each of its 200 member food banks being an independent 501(c)(3) that develops its own strategies, hires its own leaders and teams, and implements its own IT systems. Byrdak and team have also implementing a new CRM system for the national office. Analytics, CIO 100, Data Management

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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.

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Alation

JUNE 14, 2023

She adds that whenever she talks about data mesh, “I focus on the people piece of it, because it’s people who are actually going to drive it forward.” Enter the development squads To implement the data mesh, Fifth Third Bank launched 5 agile development teams known as squads. Register (and book a meeting with our team).

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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.

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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?

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AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

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