Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way. Kudu has this covered.

Data Warehouse 87

Data Warehouse Experimentation Cost-Benefit Dashboards 87

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse 53

Data Warehouse Optimization Visualization Unstructured Data 53

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. dashboards), it can leave your consumers frustrated with their experience. So let’s dive in! OLTP vs OLAP. Cluster Performance Configurations.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

CIO Business Intelligence

OCTOBER 19, 2023

With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. You can drill into data, create a variety of visualizations, and (literally) ask questions about it using AI.

Slice and Dice 111

Slice and Dice Scorecard Metrics Visualization 111

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 122

Data mining Data-driven Statistics OLAP 122

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Business intelligence examples Reporting is a central facet of BI and the dashboard is perhaps the archetypical BI tool.

Business Intelligence 135

Business Intelligence Dashboards Data mining OLAP 135

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

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.

Management 97

Management Data Warehouse Metrics Dashboards 97

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You don’t need to worry about workloads such as ETL (extract, transform, and load), dashboards, ad-hoc queries, and so on interfering with each other.

Analytics 98

Analytics Data Warehouse Testing Dashboards 98

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. The online program includes an additional nonrefundable technology fee of US$395 per course.

Big Data 121

Big Data Data Analytics Analytics Predictive Modeling 121

CIO Business Intelligence

SEPTEMBER 14, 2023

They’re often responsible for building algorithms for accessing raw data, too, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 127

Analytics Data Science Unstructured Data Data mining 127

Sisense

DECEMBER 3, 2019

The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. The first wave of digital transformations saw a dramatic decrease in data storage costs. On-demand compute resources and MPP cloud data warehouses emerged. Optimize raw data using materialized views.

Data Warehouse 90

Data Warehouse Analytics Digital Transformation Forecasting 90

Cloudera

OCTOBER 29, 2020

Adding to these innovations, we most recently released CDP Data Visualization (DV) — A native visualization tool built from our acquisition of Arcadia Data that augments data exploration and analytics across the lifecycle to more effectively share insights across the business. Accelerate Collaboration Across The Lifecycle.

Visualization 109

Visualization Machine Learning Dashboards Data Warehouse 109

Data Science 101

DECEMBER 3, 2019

Building a data strategy is a great idea. It helps to avoid many of the Challenges of a Data Science Projects. General Questions Before Starting a Data Strategy. Do you have a process for solving problems involving data? Do you have any dashboards? Do you have a data governance document?

Data Strategy 84

Data Strategy Strategy Data Warehouse Dashboards 84

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Cloudera

OCTOBER 18, 2022

However, we quickly found that our needs were more complex than the capabilities provided by the SaaS vendor and we decided to turn the power of CDP Data Warehouse onto solving our own cloud spend problem. This enabled us to ingest data faster, more reliably, and in deeper detail, while saving on licenses.

IT 87

IT Data Warehouse Dashboards Visualization 87

O'Reilly on Data

OCTOBER 19, 2021

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern.

IT 342

IT Testing Experimentation Software 342

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

CIO Business Intelligence

JULY 10, 2023

Rokita believes the key to making that transition is to stop thinking of data warehousing and AI/ML as separate departments with their own distinct systems. The data warehouse is about past data, and models are about future data. The first step was moving to the cloud.

Data Warehouse 81

Data Warehouse Cost-Benefit Unstructured Data Machine Learning 81

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. The following diagram shows a sample C360 dashboard built on Amazon QuickSight.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

CDW Research Hub

DECEMBER 4, 2019

There are many benefits of using a cloud-based data warehouse, and the market for cloud-based data warehouses is growing as organizations realize the value of making the switch from an on-premises data warehouse.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer job description.

Analytics 115

Analytics Data Science Statistics Unstructured Data 115

datapine

AUGUST 29, 2022

And with that understanding, you’ll be able to tap into the potential of data analysis to create strategic advantages, exploit your metrics to shape them into stunning business dashboards , and identify new opportunities or at least participate in the process. Best for : the new intern who has no idea what data science even means.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 72

Risk Modeling Management Metadata 72

IBM Big Data Hub

MAY 9, 2023

With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. Put AI to work in your business with IBM today IBM is infusing watsonx.ai

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

datapine

MAY 21, 2019

Also, limited resources make looking for qualified professionals such as data science experts, IT infrastructure professionals and consulting analysts impractical and worrisome. In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

AWS Big Data

NOVEMBER 13, 2023

11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture. 4:30 PM – 5:30 PM (PDT) Wynn ANT207 | Understand your data with business context. 1:00 PM – 2:00 PM (PDT) Venetian ANT201 | Accelerate innovation with real-time data.

Analytics 111

Analytics Data Lake Data Warehouse Data-driven 111

Cloudera

APRIL 1, 2024

Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics. Our customers run some of the world’s most innovative, largest, and most demanding data science, data engineering, analytics, and AI use cases, including PB-size generative AI workloads.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. In a slightly more technically-driven role, a BI developer is responsible for building, creating, or improving BI-driven solutions that help analysts transform data into knowledge, including data dashboards.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. To get started, we need an Amazon Redshift Serverless data warehouse with the Redshift ML feature enabled and an Amazon SageMaker Studio environment with access to SageMaker Feature Store.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

DataRobot Blog

FEBRUARY 28, 2023

A seamless user experience when deploying and monitoring DataRobot models to Snowflake Monitoring service health, drift, and accuracy of DataRobot models in Snowflake “Organizations are looking for mature data science platforms that can scale to the size of their entire business.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

DataKitchen

JANUARY 3, 2022

Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units. Business analysts sometimes perform data science, but usually, they integrate and visualize data and create reports and dashboards from data supplied by other groups.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245