Business leaders expect two things from IT: keep mission-critical applications available and high performing 24x7 and, if something does happen, recover to be back in business quickly and without losing any critical data so there is no impact on revenue stream. Of course, there is a gap between this de facto expectation from nontechnical business leaders and what current technology is actually capable of delivering. For mission-critical workloads, which are most often hosted on databases, organizations may choose to implement high availability (HA) technologies within the database to avoid downtime and data loss.
Traditional backup systems fail to meet the database protection and recovery requirements of modern organizations. These systems require ever-growing backup windows, negatively impact performance in mission-critical production databases, and deliver recovery time objectives (RTO) and recovery point objectives (RPO) measured in hours or even days, failing to meet the requirements of high-volume, high transactional databases -- potentially costing millions in lost productivity and revenue, regulatory penalties, and reputation damage due to an outage or data loss.
The global beauty company provides an exhilarating example of the power of context-driven commerce. When customers can rely on brands to achieve the outcomes that are important to them, brand owners can shift their focus from nonstop customer acquisition to long-term customer engagement.
The Sitecore Experience Platform and the underlying Sitecore Experience Database are foundation technologies for IT organizations wanting to implement context-driven commerce environments that function elegantly today and into the future. Sitecore puts an end to digital retailers’ obsession with cart abandonment, replacing it with opportunities to delight customers with personal, meaningful commerce offers.
Published By: Dell EMC
Published Date: Feb 07, 2018
VxRail appliances, now leveraging industry leading Dell PowerEdge servers, support business critical applications and workloads in many configurations providing required reliability, availability, flexibility and performance.
Every organization has its own set of business critical applications. For instance:
- Database applications such as Microsoft SQL server and Oracle
- Customer Relationship Management (CRM) applications such as SAP - E-mail applications such as Microsoft Exchange
-Collaboration applications, such as Microsoft SharePoint
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As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing.
To make the most of these next-generation applications, you need a next-generation database. It must handle a massive volume of data while delivering high performance to support real-time analytics. At the same time, it must provide data availability for demanding applications, scalability for growth and flexibility for responding to changes.
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements.
To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before.
These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
Flexible deployment options, licensing models help take the challenges out of change. As you move toward the cloud, you're likely planning or managing a mixed environment of on- premises and on- cloud applications. To help you succeed in this transition, you need a trans-formative, mixed-workload database that can handle a massive volume of data while delivering high performance, data availability and the flexibility to adapt respond to business changes.
The demand for databases is on the rise as organizations build next-generation business applications. NoSQL offers enterprise architecture (EA) pros new choices to store, process, and access new data formats, deliver extreme web-scale, and lower data management costs. Forrester’s 26-criteria evaluation of 15 big data NoSQL solutions will help EA pros understand the choices available and recommend the best for their organization.
This report details our findings about how each vendor fulfills our criteria and where they stand in relation to each other to help EA.
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas.
Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
The relational database has been the foundation of enterprise data management for over thirty years.
But the way we build and run applications today, coupled with unrelenting growth in new data sources and growing user loads are pushing relational databases beyond their limits. This can inhibit business agility, limit scalability and strain budgets, compelling more and more organizations to migrate to alternatives like MongoDB or NoSQL databases.
Published By: LogMeIn
Published Date: Feb 27, 2018
24/7 Self-Service Support Center: Bold360 ai’s 24/7 context driven support center was implemented, allowing users to instantly discover relevant content from the smart knowledge database. Dynamic FAQs displayed trending topics in real-time to speed up customer resolution and discoverability.
Real-Time Customer Analytics highlight unanswered questions, giving Premium Credit instant visibility of missing topics, questions driving ticket volume, and more.
Published By: IBM APAC
Published Date: Mar 19, 2018
To support ongoing expansion and transformation, the Froedtert & MCW health network needed to boost system performance and upgrade its electronic health record software.
The organization migrated to IBM® FlashSystem® and IBM Power® E870, which helped them increase their storage density by 22x and reduced cut in read-time for EHR databases by 50%.
Improved business productivity often requires more efficient IT and more efficient IT cannot be achieved without a better understanding of the way business services are run and delivered. Configuration Management Databases (CMDBs) have emerged as a central component for Information Technology Infrastructure Library (ITIL) and business service management (BSM).
Better health care at lower costs, for everyone – how do health care providers get there? Understanding the gaps in patient care, patient needs, and the geographic distribution of the patient population are important elements to consider when making decisions about improving the quality of care and reducing its costs.
To effectively analyze gaps in patient care, the data needs to be in a single place or system. However, in many organizations, data is spread across a myriad of spreadsheets and database systems. Data not organized for visual exploration and coherent analysis isn’t useful for decision making. Hence the need for visually appealing and scalable analytical tools to help organizations be more efficient, effective and economically successful.
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for
the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too.
Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and
discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the
right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
Despite heavy, long-term investments in data management, data problems at many organizations continue to grow. One reason is that data has traditionally been perceived as just one aspect of a technology project; it has not been treated as a corporate asset. Consequently, the belief was that traditional application and database planning efforts were sufficient to address ongoing data issues.
Published By: ZoomInfo
Published Date: Sep 07, 2010
Find and connect quickly with the right people, prospects, and opportunities to grow your sales pipeline and boost conversion rates. The ZoomInfo™ Database is the only source of business information combining the business web, community contributors, and professionals who post their own profiles-updated 24 hours a day, 7 days a week. Unlock the power of this data with our next-generation prospecting tool, ZoomInfo™ Pro, featuring rich segmentation, export capabilities, and list building. Add custom appends and lists to streamline revenue generation and maximize ROI. Start your free trial today.
A Java application that will successfully be able to retrieve, insert & delete data from our database which will be implemented in HBase along with.Basically the idea is to provide much faster, safer method to transmit & receive huge amounts of data
Published By: WhatCounts
Published Date: Apr 30, 2010
There's no reason overseeing and managing a million-plus subscriber email database should be a discombobulated and overbearing task. Start being an effective email marketer by creating a plan, brushing up on your skills, and cleaning house. Implementing these six simple tweaks will go a long way towards maximizing the return, response, and revenue from your email program.
Only a decade or so ago, those human resources professionals who hadn't yet found their way onto the Internet were finding themselves increasingly left out in the cold.As we slip swiftly into the second decade of the 21st century, it's those who haven't yet begun to participate in 'social media and networking' that are starting to feel the chill.
Only a decade or so ago, those human resources professionals who hadn't yet found their way onto the Internet were finding themselves increasingly left out in the cold. As we slip swiftly into the second decade of the 21st century, it's those whohaven't yet begun to participate in 'social media and networking' that are starting to feel the chill.
The SAP HANA platform provides a powerful unified foundation for storing, processing, and analyzing structured and unstructured data. It funs on a single, in-memory database, eliminating data redundancy and speeding up the time for information research and analysis.
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