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Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM
Published By: IBM     Published Date: Apr 18, 2017
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An effective big data integration solution delivers simplicity, speed, scalability, functionality and governance to produce consumable data. To cut through this misinformation and develop an adoption plan for your Hadoop big data project, you must follow a best practices approach that takes into account emerging technologies, scalability requirements, and current resources and skill levels.
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data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
IBM
Published By: IBM     Published Date: Oct 01, 2016
In the era of always-on business, enterprises need reliable, secure and consistently fast access at all times. Overlay that with the reality of how organizations combine on-premises systems with cloud-based solutions, and it’s clear that a robust, agile and flexible database platform is mandatory.
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cloud optimization, cloud efficiency, cloud management, cloud assurance, cloud visibility, enterprise management, data management
    
IBM
Published By: IBM     Published Date: May 09, 2017
How companies are managing growth, gaining insights and cutting costs in the era of big data
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
IBM
Published By: IBM     Published Date: Jun 20, 2017
Watch this on-demand webinar for a look at in-memory databases and better understand the advantages of in-memory vs. disk-based technology.
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data integration, data security, data optimization, data virtualization, in-memory, disk-based, technology
    
IBM
Published By: IBM     Published Date: May 09, 2017
DB2 delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and ease-of-use.
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db2, linux, unix, hybrid cloud, cloud solutions, enterprise data
    
IBM
Published By: IBM     Published Date: Jul 21, 2016
IBM's recently released DB2 version 11.1 for Linux, Unix and Windows (LUW) is a hybrid database that IBM says can handle transactional and analytic workloads thanks to its BLU Acceleration technology, which features an in-memory column store for analytical workloads that can scale across a massively parallel cluster.
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ibm, db2. analytics, mpp, data wharehousing
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
In the era of always-on business, enterprises need reliable, secure and consistently fast access at all times. Overlay that with the reality of how organizations combine on-premises systems with cloud-based solutions, and it’s clear that a robust, agile and flexible database platform is mandatory.
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reliability, security, consistency, database, platform, access
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
DB2 is a proven database for handling the most demanding transactional workloads. But the trend as of late is to enable relational databases to handle analytic queries more efficiently by adding an inmemory column store alongside to aggregate data and provide faster results. IBM's BLU Acceleration technology does exactly that. While BLU isn't brand new, the ability to spread the column store across a massively parallel processing (MPP) cluster of up to 1,000 nodes is a new addition to the technology. That, along with simpler monthly pricing options and integration with dashDB data warehousing in the cloud, makes DB2 for LUW, a very versatile database.
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memory analytics, database, efficiency, acceleration technology, aggregate data
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
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. In many cases, these systems are no longer up to the task—so it’s time to make a decision. Do you use more staff to keep up with the fixes, patches, add-ons and continual tuning required to make your existing systems meet performance goals, or move to a new database solution so you can assign your staff to new, innovative projects that move your business forward?
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database, growth, big data, it infrastructure, information management
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
In order to exploit the diversity of data available and modernize their data architecture, many organizations explore a Hadoop-based data environment for its flexibility and scalability in managing big data. Download this white paper for an investigation into the impact of Hadoop on the data, people, and performance of today's companies.
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hadoop, flexibility, scalability, data architecture
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
Companies today increasingly look for ways to house multiple disparate forms of data under the same roof, maintaining original integrity and attributes. Enter the Hadoop-based data lake. While a traditional on-premise data lake might address the immediate needs for scalability and flexibility, research suggests that it may fall short in supporting key aspects of the user experience. This Knowledge Brief investigate the impact of a data lake maintained in a cloud or hybrid infrastucture.
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data lake, user experience, knowledge brief, cloud infrastructure
    
IBM
Published By: IBM     Published Date: Jul 06, 2017
Known by its iconic yellow elephant, Apache Hadoop is purpose-built to help companies manage and extract insight from complex and diverse data environments. The scalability and flexibility of Hadoop might be appealing to the typical CIO but Aberdeen's research shows a variety of enticing business-friendly benefits.
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data management, yellow elephant, business benefits, information management
    
IBM
Published By: IBM     Published Date: Sep 28, 2017
Here are the 6 reasons to change your database: Lower total cost of ownership Increased scalability and availability Flexibility for hybrid environments A platform for rapid reporting and analytics Support for new and emerging applications Greater simplicity Download now to learn more!
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scalability, hybrid environment, emerging applications, rapid reporting
    
IBM
Published By: IBM     Published Date: Sep 28, 2017
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. This paper outlines what readers should consider when making a strategic commitment to a database platform that will act as a bridge from legacy environments to the cloud.
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bridging the cloud, database, hybrid cloud, cloud organization, strategic commitment
    
IBM
Published By: IBM     Published Date: Sep 28, 2017
Welcome to the era of the digital enterprise, where digital is your journey and cognitive is your destination. As business leaders, you are under growing pressure to use information to its fullest potential, delivering new customer experiences as fuel for business growth. The digital economy is changing the way we gather information, gain insights, reinvent our businesses and innovate both quickly and iteratively A hybrid cloud environment, combining traditional IT systems and public cloud, enables you to extend business processes beyond the walls of your organization. For example, many organizations use public cloud as a collaborative development environment to create innovative applications that can then be ported to an on-premises or hybrid production environment.
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cognitive era, digital, database, hybrid cloud environment, public cloud
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
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.
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database, applications, data availability, cognitive applications
    
Group M_IBM Q1'18
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
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.
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cloud, database, hybrid cloud, database platform
    
Group M_IBM Q1'18
Published By: Group M_IBM Q1'18     Published Date: Dec 19, 2017
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.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Published By: IBM     Published Date: Apr 03, 2018
Can your database systems handle data growth and keep up with performance requirements? Here are six reasons to change.
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database systems, data management, hybrid data
    
IBM
Published By: IBM     Published Date: Apr 03, 2018
This paper gives key considerations when making a strategic commitment to a database platform.
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data management, cloud, database platform
    
IBM
Published By: IBM     Published Date: Apr 03, 2018
The next generation of IBM Db2 helps organizations get more value from their big data to improve their IT economics.
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ibm, data management, db2
    
IBM
Published By: IBM     Published Date: Apr 13, 2018
Client-ready, globally applicable, a document setting out the IBM journey to GDPR Readiness
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gdpr, data, cloud, governance
    
IBM
Published By: IBM     Published Date: Apr 13, 2018
By leveraging the comprehensive capabilities in Information Governance Catalog, you are better able to align IT with your business goals.
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cloud, governance, trusted data
    
IBM
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