Sanjeev Mohan

FEBRUARY 28, 2018

The popularity of the Summit was not a surprise to me as I witnessed a pent-up surge in our clients’ and prospects’ desires to learn more about data related topics. My assessment was that many Australian clients have been slow to adopt newer technologies but are now exploring options to enhance their data infrastructure.

Management 52

Management Internet of Things Data Lake IoT 52

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. All of them generate a trail of performance-tracking data.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

Hurwitz & Associates

JULY 10, 2018

Internet-of-Things (IoT) has entered the lexicon of IT-related buzz terms in a big way over the past few years, and there is good reason for this. IoT at its foundation refers to what can literally be billions of devices spanning the globe (and beyond) that can be connected to the internet to serve a variety of purposes.

IoT 40

IoT Management Unstructured Data Internet of Things 40

Sisense

MARCH 14, 2021

When you have big data, what you really want is to extract the real value of the intelligence contained within those possibly-zettabytes of would-be information. To best understand how to do this, let’s dig into the challenges of big data and look at a wave of emerging issues.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Sisense

OCTOBER 6, 2020

When these systems connect with external groups — customers, subscribers, shareholders, stakeholders — even more data is generated, collected, and exchanged. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. Advanced technology and new approaches are needed.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Jet Global

AUGUST 14, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

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). It definitely depends on the type of data, no one method is always better than the other. This stuff works.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Jet Global

OCTOBER 2, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

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 77

Data Lake Data Analytics Analytics Data Processing 77

Data Virtualization

SEPTEMBER 16, 2020

Organizations are leveraging cloud analytics to extract useful insights from big data, which draws from a variety of sources such as mobile phones, Internet of. Organizations all over the world are migrating their IT infrastructures and applications to the cloud.

Big Data 59

Big Data Internet of Things Analytics IT 59

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics Studio uses Apache Zeppelin as the notebook, and uses Apache Flink as the stream processing engine. Kinesis Data Analytics Studio notebooks seamlessly combine these technologies to make advanced analytics on data streams accessible to developers of all skill sets.

Data Analytics 73

Data Analytics Analytics IoT Data Lake 73

O'Reilly on Data

SEPTEMBER 11, 2019

For nearly a decade, it’s provided a venue for developers, data and ML engineers, data architects, data scientists, and others to acquire or hone skills, explore provocative ideas, and network with peers. In short, what are the issues, trends, and technologies we should be watching? [1]. The term “ML” is No. What gives?

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

CIO Business Intelligence

MAY 24, 2022

Data has always been fundamental to business, but as organisations continue to move to Cloud based environments coupled with advances in technology like streaming and real-time analytics, building a data driven business is one of the keys to success. There are many attributes a data-driven organisation possesses.

Data-driven 96

Data-driven Data Lake Data Warehouse Cost-Benefit 96

IBM Big Data Hub

SEPTEMBER 11, 2023

Db2 Universal Container (also known as Db2u) is a containerization technology based on microservices architecture. Db2 Warehouse SaaS, on the other hand, is a fully managed elastic cloud data warehouse with our columnar technology. is a proven, versatile, and AI-ready solution.

Machine Learning 92

Machine Learning Cost-Benefit IoT Data Warehouse 92

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. over 2021. “The

Data Strategy 52

Data Strategy Strategy Internet of Things Data Warehouse 52

datapine

AUGUST 29, 2022

And shows how big data and the advances in analytical technologies are shaping the way the world is perceived. 2) Designing Data-Intensive Applications by Martin Kleppman. 2) Designing Data-Intensive Applications by Martin Kleppman. Not only is it comprehensive and thorough, but also comprehensible.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Sisense

MAY 11, 2021

Here at Sisense, we think about this flow in five linear layers: Raw This is our data in its raw form within a data warehouse. We follow an ELT ( E xtract, L oad, T ransform) practice, as opposed to ETL, in which we opt to transform the data in the warehouse in the stages that follow.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

OCTOBER 3, 2018

They, too, saw the enormous potential for data at scale in the enterprise. They had proven their ability to build and deliver the technology at Yahoo. In the competitive world of data management, we can each look with respect at the success of the other.

Uncertainty 75

Uncertainty IoT Risk Reporting 75