Published By: Attunity
Published Date: Nov 15, 2018
Change data capture (CDC) technology can modernize your data and analytics environment with scalable, efficient and real-time data replication that does not impact production systems.
To realize these benefits, enterprises need to understand how this critical technology works, why it’s needed, and what their Fortune 500 peers have learned from their CDC implementations. This book serves as a practical guide for enterprise architects, data managers and CIOs as they enable modern data lake, streaming and cloud architectures with CDC.
Read this book to understand:
? The rise of data lake, streaming and cloud platforms
? How CDC works and enables these architectures
? Case studies of leading-edge enterprises
? Planning and implementation approaches
With the advent of big data, organizations worldwide are
attempting to use data and analytics to solve problems previously
out of their reach. Many are applying big data and analytics
to create competitive advantage within their markets, often
focusing on building a thorough understanding of their
High-priority big data and analytics projects often target
customer-centric outcomes such as improving customer loyalty
or improving up-selling. In fact, an IBM Institute for Business
Value study found that nearly half of all organizations with active
big data pilots or implementations identified customer-centric
outcomes as a top objective (see Figure 1).1 However, big data
and analytics can also help companies understand how changes
to products or services will impact customers, as well as address
aspects of security and intelligence, risk and financial management,
and operational optimization.
High-priority big data and analytics projects often target customer-centric outcomes such as improving customer loyalty or improving up-selling. In fact, an IBM Institute for Business Value study found that nearly half of all organizations with active big data pilots or implementations identified customer-c entric outcomes as a top objective (see Figure 1).1 However, big data and analytics can also help companies understand how changes to products or services will impact customers, as well as address aspects of security and intelligence, risk and financial management, and operational optimization.
While interest in Machine Learning/Artificial Intelligence/ (ML/AI) has never been higher, the number of companies deploying it is only a subset, and successful implementations a smaller proportion still. The problem isn’t the technology; that part is working great. But the mere presence and provision of tools, algorithms, and frameworks aren’t enough. What’s missing is the attitude, appreciation, and approach necessary to drive adoption and working solutions.
To learn more, join us for this free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and panelists Jen Stirrup, Lillian Pierson, and special guest from Cloudera Fast Forward Labs, Alice Albrecht. Our panel members are seasoned veterans in the database and analytics consulting world, each with a track record of successful implementations. They’ll explain how to go beyond the fascination phase of new technology towards the battened down methodologies necessary to build bulletproof solutions th
Old-guard database providers are expensive, proprietary, have high lock-in costs, and impose restrictive licensing terms. The challenge to date has been to achieve the same performance and availability of commercial-grade databases on open source databases such as MySQL, PostgreSQL, and MariaDB.
Examine key considerations that go into any database migration decision and specific use cases—in Financial Services and Healthcare Analytics implementations—where Datavail carefully managed database migrations from traditional database providers to the cloud—and in particular Amazon Aurora.
Download the eBook to learn about:
Migration considerations and strategies including lift and shift, re-platforming, and re-factoring
Security and compliance functionality enabled by Amazon Aurora
Performance and scalability opportunities enabled by AWS
SAP HANA is a powerful, in-memory computing platform that streamlines business suite applications, analytics, planning, predictive analysis, and sentiment analysis on a single platform, so businesses can operate in real time. The design approach for enterprise-level solutions involving SAP HANA, and the best practices surrounding them, isn’t intrinsically different from the approach to any other enterprise-level solution for technology implementations. This paper is written to address those elements of good solution design and apply them to the SAP landscape, with particular focus on the SAP HANA element.
Published By: Storiant
Published Date: Mar 16, 2015
This Technology Spotlight examines the issues that are driving organizations to replace older archive and backup-and-restore systems with business continuity and always-available solutions that can scale to handle extreme data growth while leveraging a cloudbased pricing model.