In(tegrate) the Clouds

AUGUST 4, 2016

In my last post, I wrote about the new data integration requirements. In this post I wanted to share a few points made recently in a TDWI institute interview with SnapLogic founder and CEO Gaurav Dhillon when he was asked: What are some of the most interesting trends you’re seeing in the BI, analytics, and data warehousing space?

IoT 45

IoT Internet of Things Data Lake Data Warehouse 45

Cloudera

NOVEMBER 19, 2018

These data are analyzed to build a holistic picture of environmental conditions that are used to advise clients on more efficient uses of resources resulting in greater environmental sustainability. Optimizing crop rotation within small-scale agricultural operations.

Digital Transformation 40

Digital Transformation IoT Cost-Benefit Uncertainty 40

IBM Big Data Hub

JANUARY 26, 2024

This integrated solution ensures the data integration and information sharing within the company, enhancing inter-system data connectivity to improve the efficiency and quality of maintenance work. production systems, IoT platforms etc.) of the client to optimize data sharing and business synergy.

Cost-Benefit 75

Cost-Benefit Enterprise Technology KPI 75

AWS Big Data

DECEMBER 13, 2023

Using Amazon MSK, we securely stream data with a fully managed, highly available Apache Kafka service. Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Data Warehouse 102

Data Warehouse Snapshot Data Processing Management 102

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

MAY 15, 2024

Unified, governed data can also be put to use for various analytical, operational and decision-making purposes. This process is known as data integration, one of the key components to a strong data fabric. The remote execution engine is a fantastic technical development which takes data integration to the next level.

Cost-Benefit 71

Cost-Benefit Data Integration Data Architecture Manufacturing 71

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

David Menninger's Analyst Perspectives

JULY 23, 2019

Summit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.

Technology 168

Technology IoT Data Integration Big Data 168

IBM Big Data Hub

AUGUST 7, 2023

Transparency throughout the data lifecycle and the ability to demonstrate data integrity and consistency are critical factors for improvement. The ledger delivers tamper evidence, enabling the detection of any modifications made to the data, even if carried out by privileged users.

Data Governance 65

Data Governance Manufacturing Interactive IoT 65

Cloudera

FEBRUARY 4, 2019

One of the most promising technology areas in this merger that already had a high growth potential and is poised for even more growth is the Data-in-Motion platform called Hortonworks DataFlow (HDF). CDF, as an end-to-end streaming data platform, emerges as a clear solution for managing data from the edge all the way to the enterprise.

IoT 73

IoT Prescriptive Analytics Digital Transformation Internet of Things 73

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 94

Data-driven Data Lake Data Warehouse Cost-Benefit 94

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. Data Pipeline: Use Cases. Destination.

Data Warehouse 131

Data Warehouse Data Lake Visualization Big Data 131

erwin

FEBRUARY 4, 2021

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

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. Arun A K is a Big Data Specialist Solutions Architect at AWS.

Metadata 56

Metadata Data Lake Machine Learning Big Data 56

Octopai

JANUARY 31, 2022

But it is eminently possible that you were exposed to inaccurate data through no human fault.”. He goes on to explain: Reasons for inaccurate data. Integration of external data with complex structures. Big data is BIG.

Metadata 77

Metadata IT Unstructured Data IoT 77

IBM Big Data Hub

JANUARY 29, 2024

This operating model increases operational efficiency and can better organize big data. Intelligent, data integration platform example: State Bank of India State Bank of India (SBI) saw its customer base grow their wealth and found they were looking for new opportunities.

Digital Transformation 70

Digital Transformation Consulting Internet of Things Recreation/Entertainment 70

AWS Big Data

MAY 30, 2023

Traditional batch ingestion and processing pipelines that involve operations such as data cleaning and joining with reference data are straightforward to create and cost-efficient to maintain. You will also want to apply incremental updates with change data capture (CDC) from the source system to the destination.

Data Lake 82

Data Lake Data Analytics Analytics Data Processing 82

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. What is a hybrid model?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

IBM Big Data Hub

DECEMBER 11, 2023

This redundancy prevents data loss if one of the backups is comprised. Hybrid cloud also speeds disaster recovery as data is continuously replicated and refreshed, ensuring data integrity, accuracy, consistency and reliability.

Cost-Benefit 106

Cost-Benefit Data Processing Strategy Software 106

Cloudera

JUNE 25, 2019

Struggling to combat proliferating silos and control their customers’ and operations data. Overwhelmed by new data – images, video, sensor and IoT. Unprepared to meet escalating data privacy regulations. About the Author: Lakshmi Randall is Director of Product Marketing at Cloudera, the enterprise data cloud company.

Enterprise 87

Enterprise Machine Learning Recreation/Entertainment IoT 87

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected.

Management 81

Management Metadata Testing Internet of Things 81

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 9, 2024

Real-Time Analytics Pipelines : These pipelines process and analyze data in real-time or near-real-time to support decision-making in applications such as fraud detection, monitoring IoT devices, and providing personalized recommendations. As data flows into the pipeline, it is processed in real-time or near-real-time.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52