AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

Cloudera

NOVEMBER 12, 2020

Your sunk costs are minimal and if a workload or project you are supporting becomes irrelevant, you can quickly spin down your cloud data warehouses and not be “stuck” with unused infrastructure. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs.

Data Warehouse 102

Data Warehouse Reporting Risk Cost-Benefit 102

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 67

Digital Transformation Machine Learning Optimization Data Lake 67

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 109

Data Lake Analytics Dashboards Metrics 109

datapine

SEPTEMBER 29, 2022

Paired to this, it can also: Improved decision-making process: From customer relationship management, to supply chain management , to enterprise resource planning, the benefits of effective DQM can have a ripple impact on an organization’s performance. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. A brief pictorial history.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 Business Intelligence 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

IBM Big Data Hub

JULY 17, 2023

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. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 68

Machine Learning Data Warehouse Modeling Cost-Benefit 68

Andrew White

JANUARY 11, 2021

On January 4th I had the pleasure of hosting a webinar. It was titled, The Gartner 2021 Leadership Vision for Data & Analytics Leaders. This was for the Chief Data Officer, or head of data and analytics. What is your vision for D&A for small and medium enterprises? Link Data to Business Outcomes.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

FEBRUARY 8, 2022

Middlemen — data engineering or IT teams — can’t possibly possess all the expertise needed to serve up quality data to the growing range of data consumers who need it. As data collection has surged, and demands for data have grown in the enterprise, one single team can no longer meet the data demands of every department.

Data Governance 52

Data Governance Data-driven Metadata Enterprise 52

Jet Global

MAY 1, 2023

Traditional BI Platforms Traditional BI platforms are centrally managed, enterprise-class platforms. These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. addresses). Do what you expect your customers to do.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

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. Big Data is an ecosystem as well as a philosophy.

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

Cloudera

NOVEMBER 13, 2017

The net result is much improved productivity for data engineers, data scientists, and analysts. Unified – Conceptually, cloud sounds like a single place to host diverse, data-intensive functions. The ability to discover and define metadata definitions for the business is a critical enabler for self-service functions.

Analytics 40

Analytics Big Data Machine Learning Cost-Benefit 40

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. CRM platforms).

Data Processing 90

Data Processing Data Warehouse Enterprise Visualization 90

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. Experience configuration / use case deployment: At the data lifecycle experience level (e.g., Ongoing management.

Cost-Benefit 84

Cost-Benefit Data-driven Machine Learning Data Warehouse 84