Data Science 101

NOVEMBER 7, 2019

Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. R Support for Azure Machine Learning. It’s true, I saw it happen this week.

Data Science 106

Data Science Machine Learning Data Lake IoT 106

CIO Business Intelligence

DECEMBER 1, 2022

Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company.

Digital Transformation 124

Digital Transformation IoT Data-driven KPI 124

AWS Big Data

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. Finally, we can use Amazon SageMaker to build forecasting models that can predict inventory demand and optimize stock levels.

Forecasting 73

Forecasting Management IoT Data-driven 73

CIO Business Intelligence

OCTOBER 1, 2022

The company has already undertaken pilot projects in Egypt, India, Japan, and the US that use Azure IoT Hub and IoT Edge to help manufacturing technicians analyze insights to create improvements in the production of baby care and paper products. These things have not been done at this scale in the manufacturing space to date, he says.

Manufacturing 144

Manufacturing Digital Transformation IoT Internet of Things 144

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. In the long run, we see a steep increase in the proliferation of all types of data due to IoT which will pose both challenges and opportunities.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Sisense

JUNE 11, 2019

If this sounds intense, that’s because companies of all shapes and sizes who don’t reckon with the trends changing the data world will be in trouble. Trends Changing Big Data. First off, IoT, the Internet of Things. The IoT is everywhere and there are more pieces of technology connected to it every day. are all things.

Big Data 73

Big Data Slice and Dice IoT Data Lake 73

CIO Business Intelligence

SEPTEMBER 12, 2022

Collectively, the agencies also have pilots up and running to test electric buses and IoT sensors scattered throughout the transportation system. But those are broad plans that involve several transportation agencies and multimillion-dollar capital expenditures. Lookman Fazal, chief information and digital officer, NJ Transit.

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

CIO Business Intelligence

JULY 12, 2023

AI improves diaper manufacturing “All areas of P&G’s business are being impacted by emerging technologies like automation, AI, and machine learning,” says Vittorio Cretella, CIO of Procter & Gamble. P&G engineers developed a high-speed data collection system to capture data to use for training AI models.

Manufacturing 93

Manufacturing Cost-Benefit Data Lake Optimization 93

CIO Business Intelligence

APRIL 11, 2022

billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge. This next manifestation of centralized data strategy emanates from past experiences with trying to coalesce the enterprise around a large-scale monolithic data lake. over last year.

Optimization 52

Optimization Data Lake Data Strategy Internet of Things 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. HYBRID & MULTI-CLOUD INNOVATION. PEOPLE FIRST. A new award category for 2021.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

Sisense

JUNE 12, 2019

Soon after, we announced the release of Sisense Hunch which provides the ability to transform even the most massive data sets into a deep neural net which can be placed anywhere, even on an IoT device. It also deals with the volumes of training data, model ensemble performance, and dependencies on the external libraries and toolkits.

Analytics 75

Analytics Data-driven Dashboards IoT 75

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos.

Data Lake 46

Data Lake Finance Data Governance Big Data 46

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Data Lake Analytics.

Data Lake 110

Data Lake Analytics Data Warehouse Machine Learning 110

DataKitchen

JULY 27, 2023

You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 80

IoT Data Architecture Data Lake Machine Learning 80

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. This will make the data more trustworthy and reliable.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

CIO Business Intelligence

MAY 24, 2022

However, more than 99 percent of respondents said they would migrate data to the cloud over the next two years. The Internet of Things (IoT) is a huge contributor of data to this growing volume, iotaComm estimates there are 35 billion IoT devices worldwide and that in 2025 all IoT devices combined will generate 79.4

Data-driven 80

Data-driven Data Lake Data Warehouse Cost-Benefit 80

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. Amazon Kinesis Data Streams is a foundational data strategy pillar for tens of thousands of customers.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

BizAcuity

MAY 10, 2022

EC2 was a more evolved version of a Virtual Machine. Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. Microsoft launches Azure ML Studio for machine learning capabilities on the cloud. Google announces Cloud IoT. billion by 2025.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

MAY 16, 2024

H3 can also help create location-based profiling features for predictive machine learning (ML) models such as risk-mitigation models. About Amazon Redshift Thousands of customers rely on Amazon Redshift to analyze data from terabytes to petabytes and run complex analytical queries.

Data Warehouse 87

Data Warehouse Visualization Cost-Benefit Optimization 87

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. And more recently, we have also seen innovation with IOT (Internet Of Things). In data-driven organizations, data is flowing. The protection policy follows the data.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

CIO Business Intelligence

JUNE 7, 2023

Like the NFL, the NBA CTO opted to partner with Microsoft to leverage its Azure cloud platform, which Bhagavathula says contained all the digital components necessary to build the association’s streaming platform, while providing a cloud data lake and machine learning models the NBA could capitalize on for next-generation applications.

Digital Transformation 52

Digital Transformation Recreation/Entertainment Machine Learning Data Lake 52

CIO Business Intelligence

APRIL 6, 2022

Improved connectivity, including increased availability of 5G capabilities, coupled with cost-effective edge processing power, is driving the deluge of data that exists outside centralized repositories and traditional data centers. You have to use sophisticated algorithms and machine learning to make those decisions in those moments.”.

Data Strategy 52

Data Strategy Strategy Internet of Things Data Warehouse 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

erwin

DECEMBER 13, 2018

Data operations (DataOps) gains traction/will be fully optimized: Much like how DevOps has taken hold over the past decade, 2019 will see a similar push for DataOps. Data is no longer just an IT issue. As organizations become data-driven and awash in an overwhelming amount of data from multiple data sources (AI, IOT, ML, etc.),

Data Governance 91

Data Governance IoT Internet of Things Data-driven 91

Alation

FEBRUARY 20, 2020

The rise of data lakes, IOT analytics, and big data pipelines has introduced a new world of fast, big data. For EA professionals, relying on people and manual processes to provision, manage, and govern data simply does not scale. Get the latest data cataloging news and trends in your inbox.

Data Governance 52

Data Governance Data Lake Dashboards Big Data 52

CIO Business Intelligence

AUGUST 3, 2022

When Cargill started putting IoT sensors into shrimp ponds, then CIO Justin Kershaw realized that the $130 billion agricultural business was becoming a digital business. To help determine where IT should stop and IoT product engineering should start, Kershaw did not call CIOs of other food and agricultural businesses to compare notes.

Finance 131

Finance IoT Digital Transformation Sales 131

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