The role of Business Intelligence software has grown exponentially over the last decade. And as it has grown; so too has analytics-based decision making. In order to get these high-value insights; businesses need the best tools. The Ventana Research
Cognitive computing is only beginning to realize its vast potential; but already uses of critical importance have emerged: battling fatal diseases through better-informed decisions and personalized care; helping individuals gain confidence in their
In order to make wise decisions and build competitve advantage; organizations of all kinds need actionable information - that is; data placed in context so it can support decision-making. Moreover; they need to be able to make today's massive amount
Big data is of immediate relevance to the situation many organizations face today. They need to store; process and use data in significantly greater volumes than ever before. The data comes from a larger number of sources and often differs in kind fr
Applying analytics to big data can help organizations resolve many data-dependent management and operational issues encountered by both business units and the IT groups that support them. But many potential users aren�t sure precisely what big-data a
Applying analytics to big data can help organizations resolve many data-dependent management and operational issues encountered by both business units and the IT groups that support them. But many potential users aren�t sure precisely what big-data analytics is or how to use it for business advantage. The result is confusion that raises questions about the best way to proceed. This lack of clarity poses a challenge for organizations seeking competitive advantage; improved profitability; better regulatory compliance or more reliable information security. To make the right decisions; adopters need guidance based on reliable data � the kind that�s drawn from objective; in-depth research.
Tools for big-data integration must be able to work with a range of underlying architectures and data technologies that were assessed including data appliances; flat files; Hadoop and in-memory computing as well as conventional database technologies
Ventana Research Big-Data Integration focuses on the issues associated with accessing and using big data efficiently and and using technologies and tools to facilitate these efforts. This research examined the use of big-data integration in the real world to discover how organizations use it or are planning to use it effectively and derive value from it. The research investigated the range of integration technology capable enough to handle big data regardless of whether it originates in the enterprise or across the Internet. For this reason; tools for big-data integration must be able to work with a range of underlying architectures and data technologies that were assessed including data appliances; flat files; Hadoop and in-memory computing as well as conventional database technologies like RDBMS and the NoSQL and nonrelational structures of content and text.
Organizations today must utilize many kinds of information to refine their strategy and make smart decisions. Typically this information is stored in a multitude of ready-to-use formats and locations � in-house in enterprise systems; remotely; on th
Location Analytics is defined as the integration; access and use of geographic information and technology to help consumers and businesses to take action and make decisions efficiently and effectively. In addition; using this technology can add value
Cognitive computing is a new category of information technology that combines proven technologies with sophisticated analytical algorithms; natural-language- and machine-based learning and massive computer processing power to yield probabilistic res
The use of Big Data is prevalent in many companies and across industries. But even with all the tools available; there is still critical data that can escape analytics and is nearly impossible to get. Only 14% of companies being able to actually get
With the rise in the use of analytics and big data; companies are dependent on the data they collect. But if the data is not formatted in a way that analytics tools can access and use it; the results produced will be incomplete or inaccurate. This is
Data is an essential asset of all organizations. Its use impacts every aspect of a business; not least of all its profitability. Today's data comes from an array of often incompatible sources; including disparate in-house systems; cloud-based enviro
Data is fuel for today�s businesses; they cannot run without it. Like other types of fuel; it must be processed and made ready to use. Many users; however; are unfamiliar with what is required to ensure that the data available to them meets their re
Predictive analytics is a relatively straightforward idea: It is the use of past data to evaluate the likelihood of future outcomes�.
Data is a critical asset for business; but many business professionals have difficulty in getting to the data they need in a timely fashion. The inability to access data and prepare it for effective business use can impede efficiency in making decis
Organizations of all sizes and in all industries are being deluged by a torrent of data coming from a multitude of sources in many formats. Typically this data is stored in an array of disparate systems. A key technology for processing and analyzing it all is called big data.
The process of geocoding increases the quality of business information by augmenting geographic references to fully support operations and decision-making. Without the dimension added by geocoding; operational risk increases; business cycles are was
Organizations today can be overwhelmed by the flood of data they must deal with. This data arrives from many sources and also is generated internally � in both instances; rapidly; continuously and in a multiplicity of formats. Big data technology o
Cognitive systems have now become a reality; and are poised to disrupt long-held views of what computers are capable of. They will enable the emergence of new; highly productive business models; creating opportunities for some while threatening esta
Organizations need access to timely; accurate information to effectively make decisions;compete; and prosper. But doing this remains more art than science. Accommodating to this situation � being able to act faster and smarter relying on fewer human
Organizations need access to timely; accurate information to effectively make decisions;compete; and prosper. But doing this remains more art than science. Accommodating to this situation � being able to act faster and smarter relying on fewer human assets � requires properly configured; easy and immediate access to whatever information is needed to address a business need.
The Internet of Things (IoT) is a technology that extends digital connectivity to devices and sensors in homes; businesses; vehicles and potentially almost anywhere. This advance enables virtually any device to transmit its data; to which analytics can then be applied to facilitate monitoring and a range of operational functions.
The Internet of Things (IoT) is a technology that extends digital connectivity to devices and sensors in homes; businesses; vehicles and potentially almost anywhere. This advance enables virtually any device to transmit its data; to which analytics can then be applied to facilitate monitoring and a range of operational functions.
Ventana Research has completed research to benchmark organizations' use of IT analytics. The research assessed organizational maturity by examining the adequacy of people; process; information and technology competencies required to make the most effective and efficient use of analytics. The findings offer significant new insights into how analytics and the measures and metrics they provide are used to manage IT processes and operations.
Performance management consists of the strategy; methodologies and processes to manage the performance of an organization and its business network to achieve an agreed-upon set of goals and objectives. It is an undertaking that returns significant v
Enterprises today must cope with huge and rapidly increasing volumes of data generated by more sources more often and in more formats � a veritable flood of data. Contained in this data are valuable insights that can improve the business�s competiti
Big data has gained the attention of organizations seeking previously unavailable insights that help them compete better. Big data encompasses the storage and processing of any type and volume of information; structured or unstructured; arriving at
Many organizations become interested in predictive analytics as a way to enable them to adapt to a changing conditions and increasing pressure to perform. Intense global competition; new ways of conducting business (especially on the Internet) and di
Many organizations become interested in predictive analytics as a way to enable them to adapt to a changing conditions and increasing pressure to perform. Intense global competition; new ways of conducting business (especially on the Internet) and difficulty in understanding customers� behavior and preferences can challenge existing processes and delay decision-making. Businesses also must manage and use effectively a growing flood of data from more sources than ever before.
Many organizations become interested in predictive analytics as a way to enable them to adapt to a changing conditions and increasing pressure to perform. Intense global competition; new ways of conducting business (especially on the Internet) and di
Predictive analytics is quickly moving out of the shadows into the organizational spotlight. Ventana Research finds that (37%) of companies say that predictive analytics capabilities are very important; yet only(13%) of companies use specific tools t
Analytics; and in particular predictive analytics are a high priority for organizations today; for one simple reason: Those who do not invest in it will fall behind their competitors. Join industry experts Tony Cosentino from Ventana Research and Ja
Consistent; accurate product information is essential to meet the expectations of today�s customers. These demanding consumers want detailed information presented to them through whichever of the various channels; including websites and commerce sys
Deriving value from analytics requires organizations to prepare data for use; but today's explosion of data volumes; types and sources makes this a challenge�.
Deriving value from analytics requires organizations to prepare data for use; but today's explosion of data volumes; types and sources makes this a challenge�.
Deriving value from analytics requires organizations to prepare data for use; but today's explosion of data volumes; types and sources makes this a challenge�.
Integrating cloud-based data with data inside the enterprise is increasingly important to many organizations; yet most rely on exporting data to spreadsheets and text files for this purpose. But these are outdated approaches that cannot provide eith
Self-service business intelligence (BI) is all the rage these days; with self-service generally equated to usability. However; research suggests that effective self-service requires
Data increasingly provides the backbone for all business processes and systems. Thus; the need for accurate; timely information is acute. But as sources and volumes of data increase at unprecedented rates; managing it consistently and keeping data d
Consumer goods is one of the fastest changing industries in business today. The companies that comprise it frequently introduce new products and promotions and must respond with competitive speed to shifting consumer preferences. These market pressu
Geocoding enriches the geographic context of business information; especially for organizations that operate internationally and those in certain vertical industries. The location intelligence it provides can enhance the value of information that va
Cognitive systems have now become a reality; and are poised to disrupt long-held views of what computers are capable of. They will enable the emergence of new; highly productive business models; creating opportunities for some while threatening esta
Sales forecasting has been an inexact science; often depending as much on gut instinct as on data. Two reasons for this imprecision are a lack of pipeline information and a reliance on spreadsheets to create and track forecasts. The alternatives; sal
A new approach to information technology called cognitive computing promises to alter the business landscape by empowering businesses to make their business processes more effective. Relying on natural-language processing and machine-based continuou
Visual discovery enables organizations to visualize large volumes of data to find areas of opportunity and challenge. It provides a more intuitive representation of data than numbers in rows and columns. Visual discovery thus is an important additi
The marketplace is a demanding taskmaster; it insists that a business stay agile and open to new ideas and directions in order to remain competitive. This has very much been the case with location as a customer and operational attribute. With striki
Organizations are making analytics the highest-priority innovation technology. It's no wonder why. The demands placed on businesses today are unprecedented�.
Making optimal use of the huge volumes and varied forms of big data is vital for business success. Big data systems help deal with this challenge; but the data�
Analytic discovery technology enables exploratory analysis that spans multiple data sets of various sizes and structures. It is similar to data science in that both use computer science and statistical techniques
Many Organizations today are applying predictive analytics. 83% of participants in our research said that predictive analytics is important to their organization, and nearly all executives said they consider predictive analytics important.
Today the need to process and analyze the ever larger volumes of data being generated is causing many businesses to consider expanding the capabilities of their business intelligence (BI) systems.
Big data is valuable. Our benchmark research shows that using big data analytics results in better communication, better alignment of the business, a competitive advantage, better responsiveness and decreased time to market. But big data comes in many forms, from many sources and is not always easy to work with.
Data is essential to every aspect of business, and organizations that use it effectively are likely to gain advantages over competitors that do not. Information derived from this data is essential to address a variety of needs; the most common uses are to support analytics and decision-making,
Data is essential to every aspect of business, and organizations that use it effectively are likely to gain advantages over competitors that do not. Information derived from this data is essential to address a variety of needs; the most common uses are to support analytics and decision-making,
Natural language processing, including natural language queries and natural language generation, change the way users can interact with data and information. For decades BI and analytics meant tables of numbers supplemented with charts and graphs. More recently, interactive visualizations became the rage. While these presentation formats may work analysts, there are many others in the enterprise for whom they do not, and would not know what to do wit the analytic outputs even if they did. Advances in natural language processing can extend the reach of BI and analytics, making the insights available to a much broader group of users. Is your organization ready to take advantage of this new opportunity?
While the Internet of Things (IoT) may still be unfamiliar to many consumers, businesses are well aware of its potential. More than 90% of participants in our research said that IoT is important to their future operations. Most said they view IoT as very important to speed the flow of information and improve responsiveness within business processes and nearly half are using IoT in their analytics and business intelligence functions.
Product information management (PIM) landscape has changed drastically over the last few years, and many businesses are still trying to grapple with it.
Cloud computing is a major technology innovation. Many companies already use the cloud for business functions such as customer service sales marketing finance and human resources. Analytics and BI however have not migrated to the cloud as quickl...
Cloud computing is a major technology innovation. Many companies already use the cloud for business functions such as customer service sales marketing finance and human resources. Analytics and BI however have not migrated to the cloud as quickl...
Cloud computing is a major technology innovation. Many companies already use the cloud for business functions such as customer service sales marketing finance and human resources. Analytics and BI however have not migrated to the cloud as quickl...
Cloud computing is a major technology innovation. Many companies already use the cloud for business functions such as customer service sales marketing finance and human resources. Analytics and BI however have not migrated to the cloud as quickl...
"Cloud computing is changing how businesses access and use technology to innovate. It facilitates sharing of applications across the organization through various systems and collaboration on key issues and tasks. Cloud computing also enables organiza ?
Managing performance effectively requires that a company be able to provide executives managers and employees with accurate timely information and make it possible for them to work interactively with that information...
Analytic discovery technology enables exploratory analysis that spans multiple data sets of various sizes and structures. It is similar to data science in that both use computer science and statistical techniques
Dashboards combine and display information from various parts of an organization to create views of its overall status or of a particular function. For example, a dashboard of sales performance might include information about sales closed, leads generated, the pipeline of opportunities and sales performance by territory or individual. A well-designed dashboard, one that uses all relevant data and presents it in a useful, easily consumable way, is a powerful management tool.
Data lakes are important. They provide organizations the opportunity to analyze data from all sources not just one and they allow organizations to analyze data at any level of detail. These analytical capabilities enable organizations to improve business outcomes.
David Menninger shares research details on how real-world organizations are using customer-facing analytics to monetize their data.
The process of geocoding increases the quality of business information by augmenting geographic references to fully support operations and decision-making. Without the dimension added by geocoding, operational risk increases, business cycles are wasted, customer satisfaction declines and the likelihood of decisions that could be flawed increases.
Organizations around the world valiantly try each year to make it through another compensation planning cycle relying on spreadsheets. However, increasingly complex compensation process requirements make it more and more difficult for organizations to justify using “low-tech” tools. Our 2017 Total Compensation Management benchmark research finds that 83% of participants experienced some degree of paycheck errors after their compensation spreadsheets were passed on to payroll.
The transition to cloud computing has introduced new challenges for organizations seeking to satisfy the next generation of business requirements for digital transformation. Doing this is not simple; the reality is that the many disparate cloud-related technologies and the methods used to interconnect them were designed neither to interoperate easily nor to function in real time and in a secured manner.
Data lakes can provide organizations significant value and help them improve their business processes. They provide the data needed by an organization to have a complete picture of its operations and its customers allowing it to stay ahead of its competition. However, data lake architectures and technologies continue to evolve at a rapid pace. In order to stay ahead of these changes, you should adopt tools and processes that are flexible and adaptable.
This presentation by Ventana Research's David Menninger shares research details on the benefits of scalable, secure and deployment-ready platform approach to data science vs. one-off tool, proven architectures, capabilities and approaches that help kick-start and scale data science projects, tips on how to avoid issues that only manifest in production even after good training and experimentation outcomes, and more.
Hadoop 3 is the third major revision of the big data distributed computing framework. The enhancements provide additional scalability and high availability features. They also enable new workloads involving artificial intelligence, machine learning and deep learning algorithms with added support for GPUs. In addition, Hadoop 3 includes a number of enhancements for better resource and workload management capabilities.
Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected both grow. Data now streams into organizations from a variety of sources such as social media feeds and internet of things devices.
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