big data

Results 351 - 375 of 1207Sort Results By: Published Date | Title | Company Name
Published By: IBM     Published Date: Oct 13, 2016
Data quality and master data management in a hybrid environment
Tags : 
ibm, mdm, big data, ibm infosphere, knowledge management, enterprise applications, business technology, analytics
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
IBM commissioned Forrester Consulting to conduct a Total Economic Impact (TEI) study and examine the potential return on investment (ROI) enterprises may realize by leveraging IBM InfoSphere Information Integration and Governance (IIG) solutions.
Tags : 
ibm, total economic impact, tei study, roi, return on investment, big data, data governance, governance, ibm infosphere, data management, business technology, data center, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This e-book describes how a data refinery can make trusted data available quickly and easily to people and systems across your organization. It includes simple steps you can take to start exploring - and implementing - this strategy for handling the challenges of hybrid data environments.
Tags : 
ibm, trusted data, data governance, governance, big data, hybrid data environments, data management, business technology, data center, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Cloud-based data and processing services present too much opportunity for organizations to ignore. How can organizations realize the obvious financial benefits of the cloud while ensuring information culled from cloud sources is secure and trustworthy? Good hybrid information governance implies several priorities for IT and the business which are based on these foundational pillars: - Broad agreement on what information means - Clear agreement on how owned information assets will be maintained and monitored - Standard practices for securing strategic information assets - Enterprise data integration strategy
Tags : 
ibm, trusted data, big data, governance, data governance, data management, business technology, data center, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Who's afraid of the big (data) bad wolf? Survive the big data storm by getting ahead of integration and governance functional requirements Today data volumes are exploding in every facet of our lives. Business leaders are eager to harness the power of big data but before setting out into the big data world it is important to understand that as opportunities increase ensuring that source information is trustworthy and protected becomes exponentially more difficult. This paper provides a detailed review of the best practices clients should consider before embarking on their big data integration projects.
Tags : 
ibm, big data, trusted data, data management, data solutions, business technology, data center, analytics, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
IBM commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by leveraging IBM InfoSphere Information Integration and Governance (IIG) solutions.
Tags : 
ibm, forrester, data, analytics, big data, ibm information integration, governance, data management, business technology, data center, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
IBM InfoSphere Information Server connects to many new ‘at rest’ and streaming big data sources, scales natively on Hadoop using partition and pipeline parallelism, automates data profiling, provides a business glossary, and an information catalog, plus also supports IT.
Tags : 
ibm, data, analytics, big data, data integration, data management, business technology, data center, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, enterprise applications, data management, business technology, data center, analytics, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse. In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
Tags : 
ibm, ibm pure data system, big data, data analytics, analytics architecture, data warehouse, enterprise applications, data management, business technology, data center, analytics, data science
    
IBM
Published By: IBM     Published Date: Oct 13, 2016
This e-book highlights the benefits of Hadoop across several industries and explores how IBM® Biglnsights for Apache™ Hadoop® combines open source Hadoop with enterprise-grade management and analytic capabilities.
Tags : 
ibm, analytics, big data, hadoop, enterprise, ibm biginsights, apache, enterprise management, enterprise applications, data management, business technology, data science
    
IBM
Published By: IBM     Published Date: Oct 18, 2016
Informative infographic featuring case management and data capture solutions to put the customer experience first.
Tags : 
ibm, ecm, data analytics, analytics, big data, customer experience, knowledge management, enterprise applications, data management, data center, data science
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.
Tags : 
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
The bottom line is that those that have the most customer insight will win because they know what customers want. So the question is how will you get that insight? What is it that you don’t know about customers in the market(s) that you operate in? Do you have all the attributes about customers in your MDM system that could be of value to your business? Do you know about all the relationships that your customers have in your MDM system? In most cases, the answer to the above questions is no which inevitably means one thing. You need more data
Tags : 
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume.
Tags : 
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
A solid information integration and governance program must become a natural part of big data projects, supporting automated discovery, profiling and understanding of diverse data sets to provide context and enable employees to make informed decisions. It must be agile to accommodate a wide variety of data and seamlessly integrate with diverse technologies, from data marts to Apache Hadoop systems. And it must automatically discover, protect and monitor sensitive information as part of big data applications.
Tags : 
    
IBM
Published By: IBM     Published Date: Jan 27, 2017
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.
Tags : 
    
IBM
Published By: IBM     Published Date: Mar 29, 2017
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
Tags : 
cloud, analytics, data, organization, ibm
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
A big data integration platform that is flexible and scalable is needed to keep up with today’s ever-increasing big data volume. Download this infographic to find out how to build a strong foundation with big data integration.
Tags : 
big data, big data integration, scalable data
    
IBM
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.
Tags : 
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.
Tags : 
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.
Tags : 
data integration, data security, data optimization, data virtualization, database security, data migration, data assets, data delivery
    
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
Tags : 
data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
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?
Tags : 
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.
Tags : 
hadoop, flexibility, scalability, data architecture
    
IBM
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.
Tags : 
database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18
Start   Previous    8 9 10 11 12 13 14 15 16 17 18 19 20 21 22    Next    End
Search      

Related Topics

Add Your White Papers

Get your white papers featured in the Data Center Frontier Paper Library contact:
Kevin@DataCenterFrontier.com