AWS Big Data

APRIL 19, 2023

With the right analytics approach, this is possible. In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments.

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Data Warehouse Data Lake Unstructured Data Optimization 59

AWS Big Data

JUNE 21, 2023

Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. These types of queries are suited for a data warehouse. Amazon Redshift is fully managed, scalable, cloud data warehouse. To house our data, we need to define a data model.

Data Warehouse 84

Data Warehouse Data Lake OLAP Cost-Benefit 84

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. By breaking down data silos and integrating log data from multiple sources, Cloudera empowers defenders with the real-time analytics to respond to threats swiftly.

Analytics 77

Analytics Metadata Snapshot Data-driven 77

David Menninger's Analyst Perspectives

SEPTEMBER 19, 2024

As I explained in our recent Buyers Guide for Data Platforms , the popularization of generative artificial intelligence (GenAI) has had a significant impact on the requirements for data platforms in the last 18 months. Snowflake is not alone in adding support for AI workloads to its data platform.

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Data Warehouse Modeling Data Science Data Governance 130

Analytics Vidhya

JULY 22, 2022

This article was published as a part of the Data Science Blogathon Introduction Google’s BigQuery is an enterprise-grade cloud-native data warehouse. Since its inception, BigQuery has evolved into a more economical and fully managed data warehouse that can run lightning-fast […].

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Cloudera

NOVEMBER 25, 2020

In any pharma, one of the largest data problems is variety, and it has been unsolved for the last 11 years, because: . Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. The Vision of a Discovery Data Warehouse.

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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 Warehouse Business Intelligence Structured Data Data Architecture 54

AWS Big Data

OCTOBER 25, 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. Amazon Redshift’s advanced Query Optimizer is a crucial part of that leading performance.

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Statistics Data Warehouse Metadata Data Lake 82

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.

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Data Warehouse Analytics Data Lake Data Science 98

AWS Big Data

NOVEMBER 8, 2024

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. However, if you want to test the examples using sample data, download the sample data. Tahir Aziz is an Analytics Solution Architect at AWS.

Data Lake 90

Data Lake Data Warehouse Optimization Testing 90

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 99

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Analytics Vidhya

FEBRUARY 20, 2022

Introduction Apache Hive is a data warehouse system built on top of Hadoop which gives the user the flexibility to write complex MapReduce programs in form of SQL- like queries. The post Performance Tuning Practices in Hive appeared first on Analytics Vidhya.

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Data Warehouse Data Science Publishing Analytics 309

IBM Big Data Hub

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Enterprise 88

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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Optimization Strategy Data Warehouse Cost-Benefit 56

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 72

Analytics Data Warehouse Data Lake Metadata 72

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 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

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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. Grant the user role permissions for sensitive information and compliance policies.

Data Governance 102

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AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. For our solution, we use Amazon Redshift to store the data.

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AWS Big Data

AUGUST 27, 2024

Director of Product, Salesforce Data Cloud. In today’s ever-evolving business landscape, organizations must harness and act on data to fuel analytics, generate insights, and make informed decisions to deliver exceptional customer experiences. This post is co-authored by Rajkumar Irudayaraj, Sr. What is Amazon Redshift?

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Data Lake Analytics Data-driven Management 89

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

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Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

JUNE 19, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tahir Aziz is an Analytics Solution Architect at AWS.

Data Warehouse 95

Data Warehouse Testing Sales Structured Data 95

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 95

Unstructured Data Data Warehouse Structured Data Testing 95

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. These campaigns are optimized by using an AI-based bid process that requires running hundreds of analytical queries per campaign.

Big Data 73

Big Data Data Warehouse Advertising OLAP 73

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.

Technology 135

Technology Data Warehouse Big Data Machine Learning 135

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

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Data Lake Data Warehouse Unstructured Data Data Governance 96

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.

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Data Warehouse Testing Data Quality Reporting 112

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data.

Visualization 79

Visualization Dashboards Data Warehouse Metrics 79

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 144

Data mining Data-driven Statistics OLAP 144

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

OCTOBER 19, 2023

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. This enables the system to examine the data before transforming and altering it.

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AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 59

Analytics Data Lake Testing Optimization 59

Sisense

JULY 22, 2020

At Sisense, we’re dedicated to making this complex task simple, putting power in the hands of the builders of business data and strategy, and providing insights for everyone. The launch of the Google Sheets analytics template illustrates this. Understanding how data becomes insights. Connect tables.

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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. This facilitates collaboration across isolated clusters, allowing data to be shared for innovation and analytic services.

Testing 105

Testing Data Warehouse Metrics Cost-Benefit 105