AWS Big Data

MARCH 27, 2023

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.

Data Warehouse 87

Data Warehouse Management Snapshot Data Lake 87

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. EVA unifies data from MTN’s different operator systems, creating a 360° view of subscribers.

Data Lake 76

Data Lake Cost-Benefit Digital Transformation Risk 76

FineReport

MARCH 24, 2024

Data analysts interpret data using statistical techniques, develop databases and data collection systems, and identify process improvement opportunities. They should possess technical expertise in data models, database design, and data mining, along with proficiency in reporting packages, databases, and programming languages.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Corinium

APRIL 25, 2019

Then you can be more confident you’re protecting that data in the right way, in the right places, via protection policies that keep it safe without getting in the way of the business getting value from that data. In data-driven organizations, data is flowing. The protection policy follows the data.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz. The subsequent chapters focus on predictive and descriptive analysis.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

MARCH 13, 2024

Secondo Laveglia, “Quello che può accadere con la democratizzazione dell’IT è che, con i prodotti basati sui Large Language Model (LLM) scaricabili da Internet, questi modelli saranno usati facilmente dalle persone in azienda anche per singoli compiti del loro lavoro”.

Machine Learning 103

Machine Learning Deep Learning Big Data Testing 103

Domino Data Lab

APRIL 3, 2019

Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. Probably the best one-liner I’ve encountered is the analogy that: DG is to data assets as HR is to people. in lieu of simply landing in a data lake. a second priority?at

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Andrew White

JANUARY 11, 2021

How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Value Management or monetization. Product Management. Governance.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52