Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. DATA FOR ENTERPRISE AI.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

datapine

MARCH 31, 2022

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. This could involve anything from learning SQL to buying some textbooks on data warehouses.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. For IAM role ¸ choose GlueBlogRole.

Sales 52

Sales Data Warehouse Visualization Testing 52

Cloudera

MAY 2, 2018

Qonnections is the premier Business Intelligence (BI) conference that brings data lovers together to share insights and discover data in new ways. The post Disrupting Everything in BI Analytics appeared first on Cloudera Blog.

Analytics 44

Analytics Business Intelligence Data Science Data Processing 44

Cloudera

SEPTEMBER 12, 2018

It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Enterprise Machine Learning: . Technical Impact.

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. First, data isn’t created in a uniform, consistent format.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

APRIL 8, 2024

Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS Are there any constraints on the number of databases that can be hosted on an instance?  Amazon RDS for Db2 supports single-node transactional, mixed and analytics workloads. 

Snapshot 75

Snapshot Data Warehouse Data Processing Management 75

IBM Big Data Hub

JULY 17, 2023

In this blog, I will cover: What is watsonx.ai? is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. What capabilities are included in watsonx.ai? What is watsonx.data? How can you get started today?

Machine Learning 66

Machine Learning Data Warehouse Modeling Cost-Benefit 66

BizAcuity

MAY 10, 2022

And how this transformation will impact businesses in the short and long run is the main discussion in this blog. 2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. The platform is built on S3 and EC2 using a hosted Hadoop framework.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Cloudera

OCTOBER 25, 2022

The data lakehouse is gaining in popularity because it enables a single platform for all your enterprise data with the flexibility to run any analytic and machine learning (ML) use case. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Cloudera

JANUARY 3, 2019

Our pre-merger customer bases have very little overlap, giving us a considerable enterprise installed base whose demand for IoT, analytics, data warehousing, and machine learning continues to grow. It’s clear today that the data warehouse industry is undergoing a major transformation.

IoT 74

IoT Machine Learning Data Warehouse Enterprise 74

IBM Big Data Hub

SEPTEMBER 27, 2023

The attack-path view shows which hosts and assets have been impacted, while the network activity view shows if data has leaked and lateral movement has happened where malicious actions have taken place. You get near real-time visibility and insights from your ingested data.

Cost-Benefit 102

Cost-Benefit OLAP Dashboards Visualization 102

Cloudera

APRIL 14, 2021

Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. . docker build --network=host -t <company-registry>/custom-dex-spark-runtime:<version> -f Dockerfile. Why should technology partners care about CDE? References: [link].

Data Warehouse 79

Data Warehouse Data Processing Data Quality Machine Learning 79

Cloudera

APRIL 21, 2021

This cluster runs workloads for every department – from real-time user interfaces for Support to providing recommendations in the Cloudera Data Platform (CDP) Upgrade Advisor to analyzing our business and closing our books. In this blog, we discuss our journey to CDP for this critical cluster. Lessons Learned.

Testing 118

Testing Data Processing Interactive Data Warehouse 118

IBM Big Data Hub

JULY 11, 2023

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 50

Data Warehouse Testing Sales Dashboards 50

IBM Big Data Hub

MARCH 25, 2022

Advancements in software and hardware had an interplay between the rising appetite for any organization making a data-driven decision. In this blog, one of the key inventors in modern databases helps illuminate the evolution of databases, business use cases and unique perspectives being at the ground floor of innovation.

Data-driven 74

Data-driven Data Warehouse Data Processing Marketing 74

Cloudera

AUGUST 21, 2020

There are now tens of thousands of instances of these Big Data platforms running in production around the world today, and the number is increasing every year. Many of them are increasingly deployed outside of traditional data centers in hosted, “cloud” environments. Streaming data analytics. . From start to finish.

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

Cloudera

NOVEMBER 13, 2017

Cloud PaaS takes this a step further and allows users to focus directly on building data pipelines, training machine learning models, developing analytics applications — all the value creation efforts, vs the infrastructure operations. Intelligent defaults and built-in logic eliminate much of the guess work.

Analytics 40

Analytics Big Data Machine Learning Cost-Benefit 40

Cloudera

MAY 31, 2023

There are many benefits to these new services, but they certainly are not a one-size-fits-all solution, and this is most true for commercial enterprises looking to adopt generative AI for their own unique use cases powered by their data. How can enterprises address these challenges?

Enterprise 73

Enterprise Data Processing Experimentation Modeling 73

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 95

Data Warehouse Data Lake Optimization Data-driven 95

Cloudera

FEBRUARY 22, 2021

Providing a comprehensive set of diverse analytical frameworks for different use cases across the data lifecycle (data streaming, data engineering, data warehousing, operational database and machine learning) while at the same time seamlessly integrating data content via the Shared Data Experience (SDX), a layer that separates compute and storage.

Cost-Benefit 78

Cost-Benefit Data Warehouse Data Processing Data Governance 78

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. public, private, hybrid cloud)?

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

Cloudera

MAY 18, 2021

CDP Public Cloud leverages the elastic nature of the cloud hosting model to align spend on Cloudera subscription (measured in Cloudera Consumption Units or CCUs) with actual usage of the platform. Machine Learning Prototypes. Experience configuration / use case deployment: At the data lifecycle experience level (e.g.,

Cost-Benefit 84

Cost-Benefit Data-driven Data Warehouse Machine Learning 84

Cloudera

MARCH 22, 2022

That technical debt includes silo-ed data warehousing appliances, homegrown tools for data processing, or point solutions used for dedicated workloads such as machine learning. data engineering, data warehousing etc.);

Strategy 79

Strategy Cost-Benefit Risk Data Processing 79