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 78

Data Warehouse Data Lake OLAP Cost-Benefit 78

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

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.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

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

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.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

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.

Data Lake 116

Data Lake Data Processing Metadata Snapshot 116

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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.

Data Lake 112

Data Lake Analytics Dashboards Metrics 112

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. This property is set to true by default. availability.

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

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.

Data Lake 83

Data Lake Data Transformation Cost-Benefit Data-driven 83

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 112

Analytics Data Lake Data Warehouse Data-driven 112

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.

Data Lake 67

Data Lake Cost-Benefit Dashboards Data Warehouse 67

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).

Data Lake 71

Data Lake Snapshot Optimization Data Transformation 71

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 90

Data Warehouse Data Lake Analytics Data Science 90

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

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.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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.

Data Warehouse 84

Data Warehouse Data Processing Data Lake Management 84

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

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.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Use AI to tackle huge datasets.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 88

Data Lake Data Warehouse Data-driven B2B 88

AWS Big Data

MAY 16, 2024

Because of this, many organizations are utilizing them as a support geography, aggregating their data to these grids to optimize both their storage and analysis. Indexed data can be quickly joined across different datasets and aggregated at different levels of precision.

Data Warehouse 87

Data Warehouse Visualization Cost-Benefit Optimization 87

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. This introduces the need for both polling and pushing the data to access and analyze in near-real time.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. In fact, many commonly accepted best practices for designing OLTP databases could well be considered worst practices for these purely analytical systems. Analytical. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

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!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

NOVEMBER 8, 2023

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. Loading data is a key process for any analytical system, including Amazon Redshift.

Data Lake 74

Data Lake Data Warehouse Cost-Benefit Optimization 74

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 97

Data Lake Data Warehouse Testing Business Objectives 97

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?

Interactive 114

Interactive Unstructured Data Analytics Data Warehouse 114

AWS Big Data

NOVEMBER 10, 2023

Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless. Additionally, you’ll benefit from performance improvements through pushdown optimizations, further enhancing the efficiency of your operations.

Data Processing 91

Data Processing Data Lake Data Warehouse Optimization 91

BizAcuity

JULY 13, 2021

Optimize your Go To Market: The gaming business consists of various applications like the gaming platforms (Casino, Live Dealer, Poker, Sports, Bingo, etc.), account platform, payment, affiliate, loyalty system, bonus and promotion systems, financial application, CRM system, and many others. Data Enrichment/Data Warehouse Layer.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

Cloudera

JUNE 18, 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.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

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.

Data Lake 85

Data Lake Data Warehouse Machine Learning Cost-Benefit 85

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

Enterprise 83

Enterprise Data Warehouse Data Lake Optimization 83

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

Data Analytics 123

Data Analytics Analytics Recreation/Entertainment Data Lake 123

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 80

Data Lake Data Warehouse Data-driven Optimization 80