Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The destination is decided by the use case of the data pipeline.

Data Warehouse 130

Data Warehouse Data Lake Visualization Big Data 130

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 82

Analytics Data Warehouse Data Lake Metadata 82

Data Virtualization

MAY 21, 2019

The current data landscape is fragmented, not just in location but also in terms of shape and processing paradigms: data lakes, IoT architectures, noSQL and graph data stores, SaaS vendors, etc. are found coexisting with relational databases to fuel the.

Data Warehouse 45

Data Warehouse Data Lake IoT Data Governance 45

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 102

Data Warehouse KPI Optimization Cost-Benefit 102

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. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

MAY 16, 2024

As an AWS Partner, CARTO offers a software solution on the curated digital catalog AWS Marketplace that seamlessly integrates distinctive capabilities for spatial visualization, analysis, and app development directly within the AWS data warehouse environment.

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Optimization 119

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. Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. We didn’t care about what the data was,” he says. “I

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

CIO Business Intelligence

DECEMBER 1, 2022

Now halfway into its five-year digital transformation, PepsiCo has checked off many important boxes — including employee buy-in, Kanioura says, “because one way or another every associate in every plant, data center, data warehouse, and store are using a derivative of this transformation.”

Digital Transformation 139

Digital Transformation IoT KPI Data-driven 139

BizAcuity

APRIL 1, 2023

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 73

Data Warehouse Data Lake Cost-Benefit Metadata 73

Cloudera

AUGUST 9, 2022

Data platforms are no longer skunkworks projects or science experiments. As customers import their mainframe and legacy data warehouse workloads, there is an expectation on the platform that it can meet, if not exceed, the resilience of the prior system and its associated dependencies. Conclusion.

Data Lake 77

Data Lake Data Warehouse Data-driven IoT 77

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. Here they are in my order of importance (based upon my opinion). Azure Synapse.

Data Science 106

Data Science Machine Learning Data Lake Visualization 106

BizAcuity

MAY 10, 2022

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. Google launches BigQuery, its own data warehousing tool and Microsoft introduces Azure SQL Data Warehouse and Azure Data Lake Store.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 126

Analytics IoT Data-driven Snapshot 126

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 59

IoT Data-driven Data Lake Data Strategy 59

AWS Big Data

JUNE 29, 2023

In our solution, we create a notebook to access automotive sensor data, enrich the data, and send the enriched output from the Kinesis Data Analytics Studio notebook to an Amazon Kinesis Data Firehose delivery stream for delivery to an Amazon Simple Storage Service (Amazon S3) data lake. Choose Next.

Data Analytics 87

Data Analytics Analytics IoT Data Lake 87

Boris Evelson

NOVEMBER 14, 2018

Over the last five years, most large enterprises have slowly but surely matured from being data-aware to data-driven.

Data-driven 96

Data-driven Data Lake Data Warehouse Business Intelligence 96

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Alation

FEBRUARY 13, 2020

A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives. I know in February of 2017 Munich Re launched their own innovative platform as a cornerstone for analytics that involved a big data lake and a data catalog.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 112

Data Warehouse Snapshot Data Processing Internet of Things 112

CIO Business Intelligence

APRIL 6, 2022

We are centered around co-creating with customers and promoting a systematic and scalable innovation approach to solve real-world customers problems—similar to Toyota leveraging Infosys Cobalt to modernize its vehicle data warehouse into a next-generation data lake on AWS. .

Experimentation 95

Experimentation Uncertainty Data Lake Enterprise 95

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 51

Data Warehouse Analytics Big Data Data Architecture 51

CIO Business Intelligence

APRIL 6, 2022

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge.

Data Strategy 52

Data Strategy Strategy Internet of Things Data Warehouse 52

In(tegrate) the Clouds

AUGUST 4, 2016

Also driving this trend is the fact that cloud data warehousing and analytics have moved from rogue departmental use cases to enterprise deployments. The third trend is the Internet of Things (IoT). It’s already happening today in some industries with data velocity, variety, and, of course, volume.

IoT 45

IoT Internet of Things Data Lake Data Warehouse 45

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective. The analytics and data platform is powering different data needs, use cases, and growth.

Enterprise 50

Enterprise Data Lake Data mining IoT 50

Cloudera

MAY 12, 2021

This category is open to organizations that have tackled transformative business use cases by connecting multiple parts of the data lifecycle to enrich, report, serve, and predict. . DATA FOR ENTERPRISE AI. Industry Transformation: Telkomsel — Ingesting 25TB of data daily to provide advanced customer analytics in real-time .

Digital Transformation 69

Digital Transformation Machine Learning Optimization Data Lake 69

Sanjeev Mohan

FEBRUARY 28, 2018

However, most data privacy discussions veered towards the EU GDPR ([link] which is now less than 100 days away from enforcement (May 25, 2018). Data warehouse modernization was a common theme followed by developing data lakes. Migrating to the cloud was very high on everyone’s priority.

Management 52

Management Internet of Things Data Lake IoT 52

Sisense

MAY 11, 2021

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. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

CIO Business Intelligence

APRIL 22, 2024

Ma la connettività pervasiva, il cloud, l’Internet of Things (IoT) e l’Internet of Things industriale (IIoT) portano in rete i dispositivi OT e li rendono un potenziale bersaglio degli hacker, ha scritto in una recente nota la società Analysys Mason.

Data Lake 104

Data Lake Testing Management IoT 104

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. But I’ll give an example in favour of each.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

FineReport

APRIL 11, 2023

Additionally, they provide tabs, pull-down menus, and other navigation features to assist in accessing data. Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. 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. Scheduling. Target Matching.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

In(tegrate) the Clouds

DECEMBER 21, 2015

Aside from the Internet of Things, which of the following software areas will experience the most change in 2016 – big data solutions, analytics, security, customer success/experience, sales & marketing approach or something else? 2016 will be the year of the data lake.

Technology 45

Technology Internet of Things Digital Transformation Software 45

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 91

Data Lake Data Analytics Analytics Data Processing 91

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. “To

Finance 143

Finance IoT Digital Transformation Sales 143

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