data variety

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By: IBM     Published Date: Jan 02, 2014
This study highlights the phases of the big data journey, the objectives and challenges of midsize organizations taking the journey, and the current state of the technology that they are using to drive results. It also offers a pragmatic course of action for midsize companies to take as they dive into this new era of computing.
Tags : ibm, analytics, global business service, big data, business value, it professionals, volume, velocity, variety, customer analytics, trends and insights, information management, data security, integration, variety of data, analytic accelerator, infrastructure, data management, data center
     IBM
By: IBM     Published Date: May 27, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media
Tags : ibm, big data, analytics, insurance, insurance industry, big data solutions, integration, risk assessment, policy rates, customer retention, claims data, transaction data
     IBM
By: IBM     Published Date: Jul 07, 2014
The IBM Institute for Business Value conducted a global study to investigate how organizations were creating value from an ever-growing volume of data obtained from a variety of sources. This resulted from data-derived insights, which then guided actions taken at every level of the organization. The findings identified nine levers that enabled the organizations to create the most value.
Tags : ibm, midmarket, ibm global analytics study, analytics, business insights, profitability, big data, business analytics, data-driven insights, decision making
     IBM
By: IBM     Published Date: Aug 05, 2014
There is a lot of discussion in the press about Big Data. Big Data is traditionally defined in terms of the three V’s of Volume, Velocity, and Variety. In other words, Big Data is often characterized as high-volume, streaming, and including semi-structured and unstructured formats. Healthcare organizations have produced enormous volumes of unstructured data, such as the notes by physicians and nurses in electronic medical records (EMRs). In addition, healthcare organizations produce streaming data, such as from patient monitoring devices. Now, thanks to emerging technologies such as Hadoop and streams, healthcare organizations are in a position to harness this Big Data to reduce costs and improve patient outcomes. However, this Big Data has profound implications from an Information Governance perspective. In this white paper, we discuss Big Data Governance from the standpoint of three case studies.
Tags : ibm, data, big data, information, healthcare, governance, technology, it management, data management
     IBM
By: IBM     Published Date: Aug 06, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media
Tags : ibm, insurance, data, big data, analytics, solutions
     IBM
By: IBM     Published Date: Aug 08, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
Tags : big data, analytics, insurance, customer service, solutions
     IBM
By: IBM     Published Date: Aug 08, 2014
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
Tags : big data, analytics, insurance, customer service, solutions
     IBM
By: IBM     Published Date: Nov 14, 2014
Data mining uncovers patterns in data through a variety of predictive techniques. By engaging in data mining, organizations like yours gain greater insight into external conditions, internal processes, your markets – and your customers.
Tags : ibm, data mining, data management, business results, predictive intelligence, business insights
     IBM
By: IBM     Published Date: Feb 24, 2015
Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
Tags : big data, ibm, claims operations, customer service
     IBM
By: IBM     Published Date: Apr 29, 2015
First generation warehouses were not designed to manage data at today's volume or variety. Coercing older technologies to satisfy new demands can be inefficient, burdensome and costly. Read how IBM PureData System for Analytics is built for simplicity and speed.
Tags : big data, data management, hardware, business intelligence
     IBM
By: IBM     Published Date: Feb 26, 2016
With Watson Explorer, you can keep enterprise search as the foundation and transform search into Cognitive Exploration. Leveraging technological advances such as deep search and exploration, advanced content analytics, and cognitive capabilities, IBM Watson Explorer provides a unified view of the information you need, combining data from multiple internal silos and a variety of outside datasets including social media. Stop limiting your search to traditional data sources in the new, non-traditional data world.
Tags : watson explorer, ibm, deep search, content analytics, enterprise software
     IBM
By: IBM     Published Date: Jun 07, 2016
In a multi-database world, startups and enterprises are embracing a wide variety of tools to build sophisticated and scalable applications. IBM Compose Enterprise delivers a fully managed cloud data platform so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.
Tags : ibm, analytics, database, ibm compose enterprise, networking
     IBM
By: IBM     Published Date: Oct 13, 2016
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. Download this white paper to learn how.
Tags : database, big data, analytics, infrastructure, data management, data center
     IBM
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.
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     IBM
By: IBM     Published Date: Jan 27, 2017
In today’s highly distributed, multi-platform world, the data needed to solve any particular decision making need is increasingly likely to be found across a wide variety of sources. As a result, traditional manual approaches requiring prior collection, storage and integration of extensive sets of data in the analyst’s preferred exploration environment are becoming less useful. Data virtualization, which offers transparent access to distributed, diverse data sources, offers a valuable alternative approach in these circumstances.
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     IBM
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
By: IBM     Published Date: Jun 21, 2017
Today, it’s unlikely that a single database will meet all your needs. For a variety of reasons—including the need to support cloud-scale solutions and increasingly dynamic app ecosystems—startups and enterprises alike are embracing a wide variety of open source databases. These varied databases—including MongoDB, Redis and PostgreSQL— open doors to building sophisticated and scalable applications on battle-hardened, non-proprietary databases.
Tags : ibm, data base, cloud, scalability, app ecosystem
     IBM
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
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.
Tags : data management, yellow elephant, business benefits, information management
     IBM
By: IBM     Published Date: Jul 26, 2017
Business leaders are eager to harness the power of big data. However, as the opportunity increases, ensuring that source information is trustworthy and protected becomes exponentially more difficult. If not addressed directly, end users may lose confidence in the insights generated from their data—which can result in a failure to act on opportunities or against threats. Information integration and governance must be implemented within big data applications, providing appropriate governance and rapid integration from the start. By automating information integration and governance and employing it at the point of data creation, organizations can boost confidence in big data. 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 seamle
Tags : mdm, big data, automation, organization
     IBM
By: IBM     Published Date: Jul 26, 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. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
Tags : scalability, data warehousing, resource planning
     IBM
By: IBM     Published Date: Oct 13, 2017
This BARC document is the third edition of our BARC Score business intelligence vendor evaluation and ranking. This BARC Score evaluates enterprise BI and analytics platforms that are able to fulfill a broad set of BI requirements within the enterprise. Based on countless data points from The BI Survey and many analyst interactions, vendors are rated on a variety of criteria, from product capabilities and architecture to sales and marketing strategy, financial performance and customer feedback.
Tags : barc. business intelligence, analytics, customer feedback
     IBM
By: IBM     Published Date: Oct 17, 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. To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize
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     IBM
By: IBM     Published Date: Oct 26, 2017
Firms face loss of Intellectual property (IP) and breaches of sensitive data as a result of account takeover (ATO). Risk-based authentication RBA plays an important role in the identity and access management (IAM) and risk mitigation of ATO across a variety of user populations (employee-facing [B2E] users, partners, clients, and consumer/citizen-facing users).
Tags : risk based authentication, account takeover, intellectual property, sensitive data, identity management
     IBM
By: IBM     Published Date: Jul 05, 2018
Data is the lifeblood of business. And in the era of digital business, the organizations that utilize data most effectively are also the most successful. Whether structured, unstructured or semi-structured, rapidly increasing data quantities must be brought into organizations, stored and put to work to enable business strategies. Data integration tools play a critical role in extracting data from a variety of sources and making it available for enterprise applications, business intelligence (BI), machine learning (ML) and other purposes. Many organization seek to enhance the value of data for line-of-business managers by enabling self-service access. This is increasingly important as large volumes of unstructured data from Internet-of-Things (IOT) devices are presenting organizations with opportunities for game-changing insights from big data analytics. A new survey of 369 IT professionals, from managers to directors and VPs of IT, by BizTechInsights on behalf of IBM reveals the challe
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     IBM
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