Smart Data Collective

AUGUST 7, 2019

New England College talks in detail about the role of big data in the field of business. They have highlighted some of the biggest applications, as well as some of the precautions businesses need to take, such as navigating the death of data lakes and understanding the role of the GDPR. Creating predictive models.

Data Analytics 99

Data Analytics Analytics Big Data Data Lake 99

BizAcuity

JULY 13, 2021

It can reduce the whole process of transforming data to information to action in a matter of days and weeks instead of months with a unique Pay-As-You-Go licensing model that allows clients to get started with very minimal capital & operational cost. Data Enrichment/Data Warehouse Layer. Data Analytics Layer.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. They are used in everything from robotics to tools that reason and interact with humans.

Risk 78

Risk Modeling Management Metadata 78

Cloudera

MAY 12, 2021

Data Security & Governance: Merck KGaA, Darmstadt, Germany — Established a data governance framework with their data lake to discover, analyze, store, mine, and govern relevant data. Industry Transformation: Telkomsel — Ingesting 25TB of data daily to provide advanced customer analytics in real-time .

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

IBM Big Data Hub

OCTOBER 16, 2023

Banks and other financial institutions train ML models to recognize suspicious online transactions and other atypical transactions that require further investigation. Banks and other lenders use ML classification algorithms and predictive models to determine who they will offer loans to. Many stock market transactions use ML.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

Domino Data Lab

JANUARY 11, 2021

Writing data from Domino into Snowflake. Once a model has been developed, the model needs to be productionized either via an app, an API or in this case, writing model scores from the prediction model back into Snowflake so that business analyst end users are able to access predictions via their reporting tools.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

Cloudera

JULY 18, 2018

Now organizations can reap all the benefits of having an enterprise data lake, in addition to an advanced analytics solution enabling them to put machine learning and AI into action at massive scale to improve health outcomes for individuals and entire populations alike.

Machine Learning 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

DataKitchen

JANUARY 17, 2022

If data is sequestered in access-controlled data islands, the process hub can enable access. Operational systems may be configured with live orchestrated feeds flowing into a data lake under the control of business analysts and other self-service users. Data is not static. Figure 1: A DataOps Process Hub.

Experimentation 130

Experimentation Data Lake Marketing Predictive Modeling 130

AWS Big Data

NOVEMBER 14, 2023

Ten years ago, we launched Amazon Kinesis Data Streams , the first cloud-native serverless streaming data service, to serve as the backbone for companies, to move data across system boundaries, breaking data silos. Another integration launched in 2023 is with Amazon Monitron to power predictive maintenance management.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

Cloudera

NOVEMBER 18, 2020

The Advanced Analytics team supporting the businesses of Merck KGaA, Darmstadt, Germany was able to establish a data governance framework within its enterprise data lake. This enabled Merck KGaA to control and maintain secure data access, and greatly increase business agility for multiple users.

Internet Publishing and Broadcasting 119

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 119

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

Darkhorse

JULY 6, 2017

So what is data wrangling? Let’s imagine the process of building a data lake. Let’s further pretend you’re starting out with the aim of doing a big predictive modeling thing using machine learning. First off, data wrangling is gathering the appropriate data. Can you start modelling now?

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

AWS Big Data

JULY 28, 2023

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Lake 66

Data Lake Data Governance Data Warehouse Modeling 66

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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