Apache NiFi is an integrated data logistics and simple event processing platform. It provides an end-to-end platform that can collect, curate, analyze and act on data in real-time, on-premise, or in the cloud with a drag-and-drop visual interface.
This book is a must read.
Cloudera has been named as a Strong Performer in The Forrester WaveTM: Streaming Analytics, Q3 2019. We’re excited to make our debut in this Wave at, what we consider to be, such a strong position. We’ve been named one of “The 11 providers that matter most” in streaming analytics. The report states that analytics prowess, scalability, and deployment freedom are key differentiators in the evaluation across 26 criteria.
Cloudera DataFlow (CDF) is a comprehensive real-time streaming data platform that enables enterprises to address key streaming use cases across a wide range of streaming sources. CDF streamlines the process of collecting, curating, and analyzing real-time streaming data with its integrated set of products.
The Forrester Wave report recognizes Cloudera DataFlow as “more than streaming analytics.” The report states that Cloudera offers “strengths in streaming data platforms, management, security, development, extensibility and deployment.”
Download the report to read in detail about how Forrester has assessed all the vendors on their various strengths.
IT is no longer relegated to the IT group. Lines of business are building new business applications that can drive their business’s top and/or bottom lines. These applications are increasingly stateless -- meaning that they rely on their underlying operational database to manage their state and work with IT to build, deploy and manage the database infrastructure. The application development lifecycle is accelerating with the broad adoption of cloud and the rise of dbPaaS where the database is fully managed and self-optimizes for the applications. In this session, we will show you how the Cloudera Operational Database offers an accelerated on-ramp to app development by offering a modern multi-model database that eliminates infrastructure management.
During this demo, you will learn how to use the Cloudera Operational Database to:
Speakers:
Director Product Management
Cloudera
Technical Marketing
Synopsys helps development teams build secure, high-quality software, minimizing risks while maximizing speed and productivity. Synopsys, a recognized leader in application security, provides static analysis, software composition analysis, and dynamic analysis solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior.
Open source use isn’t risky, but unmanaged use of open source is.
Open source software forms the backbone of nearly every application in every industry. Chances are that includes the applications your company develops as well. If you can’t produce an accurate inventory of the licenses, versions, and patch status of the open source components in your applications, it’s time to assess your open source management policies.
This paper provides insights and recommendations to help organizations and their development and IT teams better manage the open source risk landscape. It covers:
According to SAP, more than 80% of all cyber attacks are happening on the application layer,1 specifically targeting software applications rather than the network.
Hackers take the easiest path when determining exploits and choose applications that offer the best attack surface opportunities. Those opportunities are generally created by unpatched or outdated software.
For example, Heartbleed, a dangerous security flaw, critically exposes OpenSSL, an open source project used in hundreds of thousands of applications that need to secure communications over computer networks against eavesdropping. Yet 56% of all OpenSSL versions that Cisco Security Research examined in its 2015 security report2 were still vulnerable to Heartbleed, more than two years after the Heartbleed vulnerability was first disclosed and a patched version issued.
This illustrates the difficulty organizations have in inventorying and managing open source components rather than a lack of security diligence. Without a comprehensive list of open source components in use, it is nearly impossible for any organization to identify specific applications that use vulnerable components.
This Leadership Compass from analyst firm KuppingerCole provides an overview of the market for database and big data security solutions along with guidance and recommendations for finding the sensitive data protection products that best meet client’s requirements.
The report examines a broad range of technologies, vendor product and service functionality, relative market shares, and innovative approaches to implementing consistent and comprehensive data protection across the enterprise.
From the perspectives of both data protection and regulatory compliance, it is just as critical to protect sensitive cloud-based data as it is on-premises data. One way to do this is through data encryption, yet many business’s encryption efforts are mired in fragmented approaches, siloed strategies for policy management and compliance reporting, and decentralized key management. These situations have all contributed to making encryption complicated and difficult to implement and manage.
This paper looks at 5 best practices for securing data in multi-cloud environments using the latest data encryption technologies.
When it comes to cloud environments, whether in the public cloud or a privately hosted or hybrid environment, data security and protection controls must protect sensitive data—and support constantly growing government and industry compliance requirements. Read this ebook to learn how data security and protection technologies should operate in multiple environments (physical, cloud and hybrid) at the same time.
Finding the right cloud data management solution for your business can be difficult due to the number of potential vendors and seemingly similar offerings. Without digging deeper to uncover the details, you run the risk of selecting a solution that can result in exorbitant hidden fees, unmet service level agreements (SLAs) or vendor lock in.
There are two layers to choosing a cloud data management solution. The first is choosing the right cloud with the right pricing structure. The second is a cloud provider with enterprise support ready for multi cloud deployments and artificial intelligence (AI).
In the last few years we have seen a rapid evolution of data. The need to embrace the growing volume, velocity and variety of data from new technologies such as Artificial Intelligence (AI) and Internet of Things (IoT) has been accelerated. The ability to explore, store, and manage your data and therefore drive new levels of analytics and decision-making can make the difference between being an industry leader and being left behind by the competition. The solution you choose must be able to:
Today’s businesses run on data and the leaders that drive them must embrace forward-looking data science and artificial intelligence (AI) technologies to retain competitive differentiation. They must also reliably support increasingly complex business operations without downtime. Supporting these disparate needs once required a myriad of data platforms, but that is no longer the case.
With version 11.5, IBM Db2® is extending its legacy of dependability by adding AI functionality designed to help optimize performance and support data scientists’ mission to find deeper insights. It is both powered by and built for AI
Effectively using and managing information is critical to pursuing new business opportunities, attracting and retaining customers, and streamlining operations. However, these needs create an array of workload challenges and increase demands on underlying IT infrastructure and database systems that are often not up to the task.
The question is, how will you solve for these challenges? Will you allocate more staff to keep up with patches, add-ons and continual tuning required by existing systems, or simply ignore the potential insights that lie in this wealth of new data? Many businesses are facing this challenge head-on by seeking out new solutions that leverage artificial intelligence (AI) as well as multiple capabilities and deployment options from on-premises, public and private clouds to innovate their data infrastructure and business.
When it comes to cloud environments, whether in the public cloud or a privately hosted or hybrid environment, data security and protection controls must protect sensitive data—and support constantly growing government and industry compliance requirements. Read this ebook to learn how data security and protection technologies should operate in multiple environments (physical, cloud and hybrid) at the same time.
From the perspectives of both data protection and regulatory compliance, it is just as critical to protect sensitive cloud-based data as it is on-premises data. One way to do this is through data encryption, yet many business’s encryption efforts are mired in fragmented approaches, siloed strategies for policy management and compliance reporting, and decentralized key management. These situations have all contributed to making encryption complicated and difficult to implement and manage.
This paper looks at 5 best practices for securing data in multi-cloud environments using the latest data encryption technologies.