AWS Big Data

FEBRUARY 6, 2023

He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. He has a specialty in big data services and technologies and an interest in building customer business outcomes together. Jiseong Kim is a Senior Data Architect at AWS ProServe. George Zhao is a Senior Data Architect at AWS ProServe.

Dashboards 75

Dashboards Optimization Data Lake Cost-Benefit 75

Cloudera

DECEMBER 19, 2018

The most common big data use case is data warehouse optimization. Big data architecture is used to augment different applications, operating alongside or in a discrete fashion with a data warehouse. A big data implementation may even replace a data warehouse entirely with a data lake.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

Data Virtualization

JANUARY 20, 2022

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

Data Architecture 52

Data Architecture Data Integration Technology Management 52

Data Virtualization

JANUARY 20, 2022

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”? Technologies change constantly within organizations and having a flexible architecture is key.

Data Architecture 52

Data Architecture Data Integration Technology Management 52

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

Data Architecture 82

Data Architecture Cost-Benefit Digital Transformation Business Driver 82

Cloudera

JANUARY 30, 2023

Gartner defines dark data as “The information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).”

IoT 79

IoT Data Architecture Data Lake Machine Learning 79

Cloudera

MAY 9, 2023

The company also provides a variety of solutions for enterprises, including data centers, cloud, security, global, artificial intelligence (AI), IoT, and digital marketing services. Supporting Data Access to Achieve Data-Driven Innovation Due to the spread of COVID-19, demand for digital services has increased at SoftBank.

Data Lake 86

Data Lake IoT Data Governance Data Strategy 86

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Metadata plays a key role here in discovering the data assets.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Data Virtualization

JUNE 2, 2023

The post The Energy Utilities Series: Challenges and Opportunities of Decarbonization (Post 2 of 6) appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information. Decarbonization is the process of transitioning from.

Data Integration 52

Data Integration Internet of Things Management Data Lake 52

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. In his spare time, he loves to play cricket and badminton.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

Cloudera

AUGUST 9, 2022

Standby systems can be designed to meet storage requirements during typical periods with burstable compute for failover scenarios using new features such as Data Lake Scaling. Automating the healing, recovery, scaling, and rebalancing of core data services such as our Operational Database. Conclusion.

Data Lake 75

Data Lake Data Warehouse Data-driven IoT 75

CIO Business Intelligence

MAY 12, 2022

The biggest challenge for any big enterprise is organizing the data that has organically grown across the organization over the last several years. Everyone has data lakes, data ponds – whatever you want to call them. How do you get your arms around all the data you have? So, real-time data has become air.

Testing 98

Testing Data Lake Advertising Marketing 98

Alation

APRIL 14, 2022

For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Alation

JULY 7, 2022

In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. This new role, combined with the creation of data lakes and the increasing use of cloud services, created new employment opportunities in data analytics, data architecture, and data management.

Metadata 52

Metadata Data-driven Insurance Statistics 52

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 121

Metadata Cost-Benefit Enterprise Interactive 121