The exponential growth of the Internet, driven by increasing reach and speeds have resulted in large amount of information and products available in individual websites. To keep the relevant information for the relevant audiences, metrics received through A/B tests have become the gold standard for many organizations along with some use of AI.

A/B testing is a tried and true method for deciding which business alternative is better. In our data driven world, they proliferate, and much attention has been given to most efficiently when to stop the worse alternative (which costs money). A new generation of algorithms have been developed and are widely deployed by leading data-driven companies. These “bandit algorithms” go beyond A/B testing and should be a key competency for data driven enterprises.

Radical reductions in the cost of launching satellites with sophisticated multispectral imaging technologies, coupled with advances in elastic computing and AI, has opened up exciting new possibilities. A wide variety of new applications for business impact are now possible, in areas ranging from agriculture, to quantitative finance, to lead generation. We discuss challenges and opportunities through our experiences.

Today AI/ML have become the most powerful and sort after technologies used by businesses. They have provided breakthrough insights into various applications and use cases in various industries. These range from product and services innovation, research and discovery, enhancements in customer services and productivity and efficiency etc.

The remarkable and rapid development of AI and Machine Learning techniques for supervised learning has generated a high level of interest in applying algorithms that enable companies to solve many use-cases.

Organizations face multiple challenges in data migration when embarking on their cloud journey. There is a strategic shift in data warehousing strategies as enterprises migrate their analytics databases and solutions from on-premises solutions to the cloud, in order to take advantage of the cloud’s simplicity, performance, and cost-effectiveness.

The remarkable and rapid development of AI and Machine Learning techniques for supervised learning has generated a high level of interest in applying algorithms that enable companies to solve use-cases such as predicting consumer sentiment and churn.

If you are an Enterprise Modernizing your legacy monolithic systems to support distributed, real-time event-driven architecture. A key part of build such an architecture is the development of a universal event processing framework designed to accommodate transformation into an event-driven architecture (EDA).

A Data Lake allows you to store massive amounts of data in its original form, without the need to enforce a predefined schema, enabling a far more agile and flexible architecture, which makes it easier to gain new types of analytical insights from your data.

If you are in Enterprise Modernizing your legacy monolithic systems to support distributed, there is an urgent need to implement real-time event-driven systems.

The Oracle VM virtualization solution is engineered for open cloud infrastructure. It delivers leading performance, scalability and reliability for enterprise SaaS and PaaS workloads as well as traditional enterprise applications.

The Common Vulnerabilities and Exposures Details shows that over 16,000 vulnerabilities were identified in just the last year. If you're a large enterprise with approximately majority of these vulnerabilities relevant to your systems, it might be alarming. Yet that data isn't helpful in addressing the actual challenge.

Organizations face multiple challenges in data migration when embarking on their cloud journey. There is a strategic shift in data warehousing strategies as enterprises migrate their analytics databases and solutions from on-premises solutions to the cloud, in order to take advantage of the cloud’s simplicity, performance, and cost-effectiveness.

If you are a software product vendor or a SaaS provider running or planning to run your applications/products on containers and planning to use Amazon Elastic Container Service (ECS), you will have lot of questions to ask on how to run, scale, and secure.

Most organizations struggle with managing and maintaining an ever-growing spaghetti of ETL (Extract-Transform-Load) load in their data pipelines as more source and target systems get integrated. Confluent and Apache Kakfa helps in transforming into an event-driven organization and establish a standardized, secure, reliable and scalable streaming platform both on-premises and on the cloud.

Organizations face multiple challenges in data migration when embarking on their cloud journey. There is a strategic shift in data warehousing strategies as enterprises migrate their analytics databases and solutions from on-premises solutions to the cloud, in order to take advantage of the cloud’s simplicity, performance, and cost-effectiveness.

The remarkable and rapid development of AI and Machine Learning techniques for supervised learning has generated a high level of interest in applying algorithms that enable companies to solve use-cases such as predicting consumer sentiment and churn.

A Data Lake allows you to store massive amounts of data in its original form, without the need to enforce a predefined schema, enabling a far more agile and flexible architecture, which makes it easier to gain new types of analytical insights from your data. In this conversation with you we will show you how enterprises can start building their Machine Learning Capabilities using Data Lakes.

Every day decisions are made across your organization that impact your business. Providing access to the right information in the right moment empowers everyone to make the choices that push your company ahead.

Every day decisions are made across your organization that impact your business. Providing access to the right information in the right moment empowers everyone to make the choices that push your company ahead.

The Common Vulnerabilities and Exposures Details shows that over 16,000 vulnerabilities were identified in just the last year. If you’re a large enterprise with approximately majority of these vulnerabilities relevant to your systems, it might be alarming. Yet that data isn’t helpful in addressing the actual challenge. Regardless of the numbers, you need to resolve the underlying problem. And to do this, you need to align your best practices for patch management to close the gap on your vulnerable systems.

If you are a company looking to remain competitive and take the first steps towards the inevitable AI transformation that is already taking place in so many industries, you will have a lot of questions about how to operationalize AI initiatives that drive immediate business value and put you on the path to ongoing longer term transformation.

If you are a software product vendor or a SaaS provider running or planning to run your applications/products on containers and planning to use Amazon Elastic Container Service (ECS), you will have lot of questions to ask on how to run, scale, and secure.

AWS Systems Manager centralizes operational data from multiple AWS services and automates tasks across AWS resources. Many enterprises often bring their traditional on-premises toolset to manage their cloud and hybrid environments; however, managing cloud and hybrid environments using a traditional toolset is complex and costly.

Organizations face multiple challenges in data migration when embarking on their cloud journey. There is a strategic shift in data warehousing strategies as enterprises migrate their analytics databases and solutions from on-premises solutions to the cloud, in order to take advantage of the cloud's simplicity, performance, and cost-effectiveness.

DevOps is the combination of cultural philosophies,practices and tools that increases an organization's ability to deliver applications and services at high velocity. This speed enables organizations to better serve their customers and compete more effectively in the market.Continuous Integration and Continuous Delivery (CI/CD), and Infrastructure as a Code(IaaC) is a key philosophy in DevOps.

A Data Lake allows you to store massive amounts of data in its original form, without the need to enforce a predefined schema, enabling a far more agile and flexible architecture, which makes it easier to gain new types of analytical insights from your data. In this conversation with you we will show you how […]

The remarkable and rapid development of AI and Machine Learning techniques for supervised learning has generated a high level of interest in applying algorithms that enable companies to solve use-cases such as predicting consumer sentiment and churn. However, in our experience, less attention has been paid to the deeper questions of whether pure prediction methods […]

Oracle Integration Cloud helps businesses in simplifying and build integrations in the cloud, letting them connect securely to applications and services both in the cloud and on-premises. Join us for our event on Oracle Integrated Cloud on 7th February 2018.

You know how critical your data is to your business – and that’s why it’s crucial to avoid downtime. Because downtime can mean lost revenue, lost customer confidence and a lot of lost productivity. But there’s a simple, optimized and affordable solution: the new Oracle Database Appliance X6-2. It’s an integrated solution of database and […]

CT and AWS invite you to join this session which emphasizes on the way we have leveraged our Continuous Integration

As the companies today are directed at overhauling their Infrastructure and IS Applications considering the pace at which they are growing.

In 2020 the world will generate 50 times the amount of data as in 2011.

Join Cambridge Technology Enterprises at the Oracle FY15 India Partner Forum in Bangkok, Thailand.