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 82

Data Warehouse Data Processing Data Lake Management 82

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 89

Data Warehouse Analytics Metrics Snapshot 89

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

Cloudera

SEPTEMBER 29, 2020

Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . Cloudera Data Warehouse vs HDInsight.

Data Warehouse 116

Data Warehouse Metadata Data-driven Machine Learning 116

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

Data Science Data Lake Data mining Deep Learning 319

BizAcuity

APRIL 1, 2023

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. The BYNET interconnect supports up to 512 nodes.

Optimization 52

Optimization Data Warehouse Management Modeling 52

Cloudera

DECEMBER 11, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 CDW is an analytic offering for Cloudera Data Platform (CDP). Cloudera Data Warehouse vs EMR.

Data Warehouse 106

Data Warehouse Metadata Machine Learning Measurement 106

BizAcuity

SEPTEMBER 22, 2022

Teradata is based on a parallel Data Warehouse with shared-nothing architecture. Data is stored in a row-based format. It supports a hybrid storage model in which frequently accessed data is stored in SSD whereas rarely accessed data is stored on HDD. Not being an agile cloud data warehouse.

Optimization 52

Optimization Data Warehouse Management Modeling 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

Cloudera

DECEMBER 21, 2023

Some are returning errors that are difficult to find—and if you’re missing KPIs you have to fix, optimize, and measure every bit of code, which can take a considerable amount of time and trial and error. Optimizing any query Sometimes we are looking at a query that just seems overly complex. What a nightmare!

Optimization 67

Optimization Sales Data Warehouse Measurement 67

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

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 110

Interactive Unstructured Data Analytics Data Warehouse 110

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.

Data Warehouse 67

Data Warehouse Cost-Benefit Metadata Management 67

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 135

Analytics Data Science Unstructured Data Data mining 135

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 69

Data Warehouse Metadata Interactive Dashboards 69

CIO Business Intelligence

MARCH 9, 2022

Data-driven organizations understand that data, when analyzed, is a strategic asset. It forms the basis for making informed decisions around product innovation, dynamic pricing, market expansion, and supply chain optimization. Another option was to leverage the compute, storage and analytics services of public cloud providers.

Data-driven 110

Data-driven Analytics Machine Learning Optimization 110

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

Data Warehouse 43

Data Warehouse Unstructured Data Internet of Things Enterprise 43

Sisense

JULY 7, 2020

Today’s organizations are more data-driven than ever. Over a third of respondents to our State of Analytics and BI survey reported that they are currently focused on growing their use of analytics across their businesses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

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

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. 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. We think of this concept as inside-out data movement.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

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.

Data Warehouse 52

Data Warehouse Analytics Data mining Business Intelligence 52

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

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 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

FEBRUARY 1, 2024

Trade quality and optimization – In order to monitor and optimize trade quality, you need to continually evaluate market characteristics such as volume, direction, market depth, fill rate, and other benchmarks related to the completion of trades. This will be your OLTP data store for transactional data. version cluster.

Data Warehouse 120

Data Warehouse Dashboards Risk Management Risk 120

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses.

Data Warehouse 89

Data Warehouse Data-driven Machine Learning B2B 89

Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. In financial services, fast-moving data is critical for real-time risk and threat assessments. The need for real-time decision support and automation is clear.

Data Warehouse 85

Data Warehouse Experimentation Cost-Benefit Dashboards 85

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

JUNE 28, 2023

For example, customers told us that they want to ingest streaming data into their data stores for doing analytics—all without delving into the complexities of ETL. They can connect to multiple data streams and pull data directly into Amazon Redshift without staging it in Amazon Simple Storage Service (Amazon S3).

Analytics 66

Analytics Data Warehouse Data Lake Data-driven 66

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.

Analytics 109

Analytics IoT Data-driven Snapshot 109

Analytics Vidhya

JULY 20, 2022

Before designing an ETL job, choosing optimal, performant, and cost-efficient tools […]. The post Developing an End-to-End Automated Data Pipeline appeared first on Analytics Vidhya. Be it a streaming job or a batch job, ETL and ELT are irreplaceable.

Data Science 352

Data Science Optimization Publishing Analytics 352

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. They should also provide optimal performance with low or no tuning.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

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 89

Data Processing Data Lake Data Warehouse Optimization 89

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 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Jet Global

MAY 21, 2019

Jet Analytics provides users with several data sources and data structures to choose from when building reports or dashboards. But how do you decide when to choose your live database, your data warehouse or your cubes? Webinar Date: Thurs June 13th, 2019 | 9:00am – 9:30am PDT. Register Now!

Reporting 75

Reporting Optimization Data Warehouse Dashboards 75

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

IBM Big Data Hub

OCTOBER 1, 2018

The IBM Integrated Analytics System (IIAS), is a unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark.

Data Warehouse 72

Data Warehouse Machine Learning Big Data Optimization 72

AWS Big Data

MAY 17, 2023

Credit: Phil Goldstein Jerry Wang, Peloton’s Director of Data Engineering (left), and Evy Kho, Peloton’s Manager of Subscription Analytics, discuss how the company has benefited from using Amazon Redshift. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 108

Data Warehouse Cost-Benefit Sales Data-driven 108