AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

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Data Lake Data Warehouse Metadata Data Architecture 97

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 340

Data Science Data Lake Data mining Deep Learning 340

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.

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Data Lake Sales Data Warehouse Snapshot 107

AWS Big Data

JUNE 21, 2023

This approach comes with a heavy computational cost in terms of processing and distributing the data across multiple tables while ensuring the system is ACID-compliant at all times, which can negatively impact performance and scalability. These types of queries are suited for a data warehouse. This is called index overloading.

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Data Warehouse Data Lake OLAP Cost-Benefit 83

BI-Survey

JANUARY 15, 2023

Data architecture is a topic that is as relevant today as ever. It is widely regarded as a matter for data engineers, not business domain experts. Statements from countless interviews with our customers reveal that the data warehouse is seen as a “black box” by many and understood by few business users. But is it really?

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Data Warehouse IT Data Architecture Measurement 52

Smart Data Collective

MARCH 30, 2022

Azure Data Lake Storage Gen2 is based on Azure Blob storage and offers a suite of big data analytics features. If you don’t understand the concept, you might want to check out our previous article on the difference between data lakes and data warehouses. Determine your preparedness.

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Data Lake Cost-Benefit Data Warehouse Big Data 100

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 56

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Data Lake Data Processing Metadata Snapshot 94

AWS Big Data

MAY 20, 2024

Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS. I mtiaz (Taz) Sayed is the WW Tech Leader for Analytics at AWS.

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Data Lake Cost-Benefit Big Data Data Warehouse 79

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

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Data Lake Metadata Optimization Statistics 117

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Warehouse Data Lake Analytics Machine Learning 104

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 57

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 57

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

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Data Lake Data Warehouse Marketing Management 88

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. The SQL query language used to extract data for reporting could also potentially be used to insert, update, or delete records from the database.

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Data Lake OLAP Data Warehouse Unstructured Data 88

BI-Survey

AUGUST 21, 2020

Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? What role do technology and IT infrastructure play?

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Data Warehouse Data Lake Data Governance Data Architecture 98

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

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Data Lake Data Processing Metadata Snapshot 121

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. However, our consumers pushed us for better query performance and enhanced analytical capabilities.

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Data Warehouse Data Lake Management Data-driven 87

Jet Global

NOVEMBER 5, 2020

To enhance security, Microsoft has decided to restrict that kind of direct database access in D365 F&SCM and replace it with an abstraction layer comprised of something called “data entities”. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting has traditionally relied on a data warehouse.

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Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

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Data Lake Cost-Benefit Dashboards Data Warehouse 71

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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Data Warehouse Management Snapshot Data Lake 87

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 99

Analytics Vidhya

JANUARY 2, 2023

Introduction Delta Lake is an open-source storage layer that brings data lakes to the world of Apache Spark. Delta Lakes provides an ACID transaction–compliant and cloud–native platform on top of cloud object stores such as Amazon S3, Microsoft Azure Storage, and Google Cloud Storage.

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Data Lake Analytics IT Data Warehouse 277

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

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Data Lake Data Transformation Cost-Benefit Data-driven 87

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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Data Lake Analytics Dashboards Metrics 117

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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Data Warehouse Data Processing Data Lake Management 89

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

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Data Warehouse Data Lake OLAP Data-driven 52

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 Data Lake Analytics Data Science 95

AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

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Data Lake Metadata Testing Data Warehouse 85

AWS Big Data

FEBRUARY 12, 2024

Objective Gupshup wanted to build a messaging analytics platform that provided: Build a platform to get detailed insights, data, and reports about WhatsApp/SMS campaigns and track the success of every text message sent by the end customers. Additionally, extract, load, and transform (ELT) data processing is sped up and made easier.

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Data Warehouse Analytics Snapshot Cost-Benefit 104

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?

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Analytics Data Lake Data Warehouse Data-driven 113

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable). Most databases use a transaction log to record changes made to the database.

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Data Lake Snapshot Optimization Data Transformation 75

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. Expiration actions – These actions define when objects expire. Amazon S3 deletes expired objects on your behalf.

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Data Lake Snapshot Metadata Optimization 86

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 95

Data Analytics Analytics Data Warehouse Data Lake 95

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.

Analytics 175

Analytics Data Warehouse Business Intelligence Software 175

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 92

Data Warehouse Cost-Benefit Consulting Interactive 92

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

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Data Lake Data Warehouse Big Data Machine Learning 73

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