In recent years, many enterprises have migrated data platform workloads from on-premises infrastructure to cloud environments, attracted by the promised benefits of greater agility and lower costs. The scale of cloud data platform adoption is illustrated by Ventana Research’s Data Lakes Dynamic Insights research: For two-thirds (66%) of participants, the primary data platform used for analytics is cloud based. As the quantity and importance of the data platform workloads deployed in the cloud...
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Topics:
business intelligence,
Cloud Computing,
data operations,
robotic automation,
analytic data platforms,
Analytics and Data,
AI and Machine Learning
In today’s organization, the myriad of analytics and permutations of dashboards challenge workers’ ability to take contextual actions efficiently. Unfortunately, conventional wisdom for investing in analytics does not recognize the benefits of empowering the workforce to understand the situation, examine options and work together to make the best possible decision.
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Topics:
business intelligence,
Analytics,
Data,
Digital Technology,
analytic data platforms,
Analytics and Data,
AI and Machine Learning
The data catalog has become an integral component of organizational data strategies over the past decade, serving as a conduit for good data governance and facilitating self-service analytics initiatives. The data catalog has become so important, in fact, that it is easy to forget that just 10 years ago it did not exist in terms of a standalone product category. Metadata-based data management functionality has had a role to play within products for data governance and business intelligence for...
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Topics:
business intelligence,
Data Governance,
Data Management,
Data,
data operations,
Analytics and Data
I recently wrote about the growing range of use cases for which NoSQL databases can be considered, given increased breadth and depth of functionality available from providers of the various non-relational data platforms. As I noted, one category of NoSQL databases — graph databases — are inherently suitable for use cases that rely on relationships, such as social media, fraud detection and recommendation engines, since the graph data model represents the entities and values and also the...
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Topics:
business intelligence,
Analytics,
Cloud Computing,
Data,
Digital Technology,
Analytics and Data,
AI and Machine Learning
I previously explained how the data lakehouse is one of two primary approaches being adopted to deliver what I have called a hydroanalytic data platform. Hydroanalytics involves the combination of data warehouse and data lake functionality to enable and accelerate analysis of data in cloud storage services. The term data lakehouse has been rapidly adopted by several vendors in recent years to describe an environment in which data warehousing functionality is integrated into the data lake...
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Topics:
business intelligence,
Analytics,
Data,
data lakes
Despite all the advances organizations have made with respect to analytics, our most recent research shows the majority of the workforce in the majority of organizations are not using analytics and business intelligence (BI). Less than one-quarter (23%) report that one-half or more of their workforce is using analytics and BI. This is a problem. It means organizations are not enabling their workforce to perform at peak efficiency and effectiveness. It means the workforce in many organizations...
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Topics:
Sales,
business intelligence,
embedded analytics,
Analytics,
Data,
Sales Performance Management,
Digital Technology,
Digital Commerce,
natural language processing,
Subscription Management,
partner management,
Collaborative & Conversational Computing
As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...
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Topics:
business intelligence,
Analytics,
Data,
data lakes,
data operations,
AI and Machine Learning
Organizations have become more agile and responsive, in part, as a result of being more agile with their information technology. Adopting a DevOps approach to application deployment has allowed organizations to deploy new and revised applications more quickly. DataOps is enabling organizations to be more agile in their data processes. As organizations are embracing artificial intelligence (AI) and machine learning (ML), they are recognizing the need to adopt MLOps. The same desire for agility...
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Topics:
business intelligence,
Analytics,
Data Governance,
Data,
Digital Technology,
data operations
Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions. The product features fact boards, annotations and the ability to share facts and analysis across teams. Data teams and analysts start by creating common definitions of key performance...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data,
AI and Machine Learning
I am happy to share insights gleaned from our latest Value Index research, an assessment of how well vendors’ offerings meet buyers’ requirements. The 2021 Ventana Research Value Index: Collaborative Analytics and Data is the distillation of a year of market and product research by Ventana Research. See our prior post for a description of our methodology and included vendors.
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Topics:
business intelligence,
Analytics,
Collaboration,
Data Preparation,
Information Management,
Data,
Digital Technology,
natural language processing,
mobile computing
I am happy to share insights gleaned from our latest Value Index research, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Mobile Analytics and Data 2021 is the distillation of a year of market and product research by Ventana Research. See our prior post for a description of our methodology and which vendors are included.
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Topics:
business intelligence,
Analytics,
Collaboration,
Data Governance,
Information Management,
Data,
Digital Technology,
natural language processing,
mobile computing
We are happy to share some insights about TIBCO Spotfire drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
AI and Machine Learning
We are happy to share some insights about Sisense drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
natural language processing,
AI and Machine Learning
We are happy to share some insights about Infor Birst drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Preparation,
Data,
Information Management (IM),
natural language processing,
AI and Machine Learning
We are happy to share some insights about SAP drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
natural language processing,
AI and Machine Learning
We are happy to share some insights about Qlik drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
Information Management (IM),
natural language processing,
AI and Machine Learning
We are happy to share some insights about Information Builders’ WebFOCUS Business Intelligence and Analytics Platform drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
natural language processing,
AI and Machine Learning
We are happy to share some insights about MicroStrategy drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
natural language processing,
AI and Machine Learning
Organizations are becoming more and more data-driven and are looking for ways to accelerate the usage of artificial intelligence and machine learning (AI/ML). Developing and deploying AI/ML models can be complicated in many ways, often involving different tools and services to manage these solutions from end to end. Accessing and preparing data is the most common challenge organizations face in this process, and consequently, AI/ML vendors typically incorporate tools to address this part of the...
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Topics:
business intelligence,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
AI and Machine Learning
Process-mining software isn’t exactly new, but it’s also not widely known in the software technology market. The discipline has been around for at least a decade, but is generating more interest these days with both specialist vendors and major enterprise software vendors offering process-mining products and services. We assert that through 2022, 1 in 4 organizations will look to streamline their operations by exploring process mining.
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Topics:
business intelligence,
Analytics,
Digital Technology,
AI and Machine Learning
Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management. The goal is to understand how to manage the growing volume of data in real time, across all sources and platforms, and use it to inform, streamline and transform internal operations. Over the years, the adoption of cloud computing has gained momentum with more and more organizations trying to make use of applications, data, analytics...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Information Management,
Internet of Things,
Data,
natural language processing,
AI and Machine Learning
Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.
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Topics:
business intelligence,
Analytics,
Data Governance,
Data Preparation,
Information Management,
Data,
data lakes
Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
Information Management (IM),
data lakes,
AI and Machine Learning
Every organization performing analytics with multiple employees needs to collaborate. They should be collaborating in the analytics process and in communicating the results of those analyses. As I continue my evaluation of analytics and data vendors, I have to admit some disappointment at the level of collaborative capabilities some analytics vendors provide. To be fair, the level of capabilities vary widely, but I expected collaborative capabilities to be more uniformly available as a standard...
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Topics:
business intelligence,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
Digital Technology,
collaborative computing
I’ve written before about blockchain’s significant potential. A lot of the current discussion on the topic centers on cryptocurrencies and financial trading platforms, both of which are already in operation. However, my focus is on its applicability to business generally, especially in B2B commerce, where I believe there is significant potential for it to serve as a universal data connector. There’s also a great deal of potential for blockchain to provide individuals with greater power in ...
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Topics:
Sales,
Human Capital Management,
business intelligence,
Collaboration,
Internet of Things,
Data,
Product Information Management,
Digital Commerce,
Enterprise Resource Planning,
blockchain,
candidate engagement,
collaborative computing,
continuous supply chain
Sage Intacct recently hosted its annual user group meeting, Advantage, and earlier this year met with industry analysts. Both meetings shed light on how the company is addressing two key opportunities. One is building a robust offering to address rapidly evolving technology requirements for the Office of Finance. The other is broadening the scope of its offering to address the financial management and administration needs of its customers.
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Topics:
Office of Finance,
business intelligence,
Financial Performance Management,
ERP and Continuous Accounting,
robotic finance,
Predictive Planning,
revenue and lease accounting,
AI and Machine Learning
For interactions with customers to go well, organizations must manage an ever-increasing array of engagement channels. Our research finds that organizations expect to see interaction volumes increase on all channels, especially digital ones such as text-based messaging, chat, mobile and social apps. Unfortunately, the systems that manage these channels are typically disparate and uncoordinated and may not use the same underlying technology. This makes it difficult for organizations to...
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Topics:
Customer Experience,
Voice of the Customer,
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Internet of Things,
Contact Center,
Data,
Digital Technology,
Digital Commerce,
blockchain,
natural language processing,
data lakes,
Intelligent CX,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
Today’s intense competition requires that companies know as much as they can about their customers in order to anticipate their needs and deliver a superior customer experience. However, many organizations struggle to do this well. Implementing initiatives to improve customer value across any department or process involving customers requires both in-depth visibility into current operations and excellent metrics.
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Topics:
Customer Experience,
Voice of the Customer,
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Internet of Things,
Contact Center,
Data,
Digital Commerce,
blockchain,
natural language processing,
data lakes,
Intelligent CX,
Conversational Computing,
collaborative computing,
mobile computing,
Subscription Management,
agent management,
extended reality,
AI and Machine Learning
Organizations’ use of data and information is evolving as the amount of data and the frequency with which that data is collected increase. Data now streams into organizations from myriad sources, among them social media feeds and internet-of-things devices. These seemingly ever-increasing volumes of devices and data streams offer both challenges and opportunities to capture information about a business and improve its operations.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Lake,
Information Management,
Internet of Things,
Data,
Digital Technology,
AI and Machine Learning
It’s no secret that employees are overwhelmed. They’re having to use an array of systems and enterprise tools in the flow of work and deal with an explosion of email messages and other communications requiring some response or action and mountains of content to consume and retain. On top of these time demands, employees must try to keep up with a staggering amount of organizational change.
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Topics:
Human Capital Management,
business intelligence,
Learning Management,
Information Management,
Workforce Management,
Digital Technology,
natural language processing,
AI and Machine Learning
The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any appropriately designed device can generate and transmit data about its operations, which can facilitate monitoring and a range of automatic functions. To do this IoT requires a set of event-centered information and analytic processes that enable people to use that event information to make...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Internet of Things,
Data,
Information Management (IM),
Digital Technology,
data lakes,
AI and Machine Learning
I am happy to offer some insights on Yellowfin drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. TheVentana Research Value Index: Analytics and Business Intelligence 2019is the distillation of a year of market and product research efforts byVentana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the...
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Topics:
Data Science,
Mobile Technology,
business intelligence,
Analytics,
Cloud Computing,
Collaboration,
Yellowfin,
Digital Technology
I am happy to offer some insights on Information Builders drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth...
Read More
Topics:
Data Science,
business intelligence,
Mobile Intelligence,
Analytics,
Cloud Computing,
Collaboration,
Digital Technology
I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research, we apply a structured research methodology built on evaluation categories that are designed to...
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Topics:
Data Science,
business intelligence,
Mobile Intelligence,
Analytics,
Cloud Computing,
Collaboration,
Digital Technology
Ventana Research provides unique insight into the analytics and business intelligence (BI) industry. This is important, as its processes and technology play an instrumental role in enabling an organization’s business units and IT to utilize its data in both tactical and strategic ways to perform optimally. To accomplish this, organizations must provide technology that can access the data, generate and apply insights from analytics, communicate the results and support collaboration as needed.
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Topics:
Data Science,
business intelligence,
Mobile Intelligence,
Analytics,
Cloud Computing,
Collaboration,
Digital Technology
Was accounting ever cool? Well, yes, in a nerdy sort of way. Double-entry bookkeeping, codified in the 15th century by Fra Luca Pacioli, a Franciscan friar and pal of Leonardo Da Vinci, was essential for the expansion of trade and the creation of the modern corporation. Bookkeeping and accounting were as important to economic development as two other financial inventions – insurance and fractional reserve banking. Double-entry bookkeeping is an elegant system, simple yet powerful. It supports...
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Topics:
Big Data,
Office of Finance,
Continuous Planning,
business intelligence,
Analytics,
Financial Performance Management,
Enterprise Resource Planning,
ERP and Continuous Accounting
I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.
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Topics:
Big Data,
Data Science,
Mobile Technology,
business intelligence,
Analytics,
Cloud Computing,
Collaboration,
Data Governance,
Data Integration,
Data Preparation,
Internet of Things,
Information Optimization,
Machine Learning and Cognitive Computing,
Machine Learning Digital Technology