Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically.
Read More
Topics:
embedded analytics,
Analytics,
Business Intelligence,
AI and Machine Learning
When joining Ventana Research, I noted that the need to be more data-driven has become a mantra among large and small organizations alike. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. Being data-driven is clearly something to aspire to. However, it is also a somewhat vague concept without clear definition. We know data-driven organizations when we see them...
Read More
Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data,
Digital Technology,
natural language processing,
data lakes,
data operations,
Digital Business,
Streaming Analytics,
data platforms,
Analytics & Data,
Streaming Data & Events,
AI and Machine Learning
OneStream offers a platform designed to serve the needs of accounting and financial planning and analysis organizations. The software handles financial close and consolidation, planning and budgeting, analysis and reporting. For me, the most significant announcement at the company’s recent user conference was the unveiling of its Sensible ML (Machine Learning) offering, which is in limited general release. I’ve commented on the importance of artificial intelligence in business applications, and...
Read More
Topics:
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
digital finance,
profitability management,
AI and Machine Learning
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...
Read More
Topics:
business intelligence,
Analytics,
Cloud Computing,
Data,
Digital Technology,
data platforms,
Analytics & Data,
AI and Machine Learning
A few years ago – somewhat tongue in cheek – I began using the term “data pantry” to describe a type of data store that’s part of a business application platform, created for a specific set of users and use cases. It’s a data pantry because, unlike a general-purpose data store such as a data warehouse, everything the user needs is readily available and easily accessible, with labels that are immediately recognized and understood.
Read More
Topics:
Data Management,
Business Planning,
Financial Performance Management,
ERP and Continuous Accounting,
digital finance,
AI and Machine Learning
Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify...
Read More
Topics:
business intelligence,
embedded analytics,
Data Governance,
Data Management,
natural language processing,
data operations,
Streaming Analytics,
operational data platforms,
AI and Machine Learning
I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing business intelligence (BI) and data science tools to analyze data in data lakes. Interactive SQL query...
Read More
Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data,
Digital Technology,
data lakes,
data operations,
data platforms,
Analytics & Data,
AI and Machine Learning
I’ve never been a fan of talking about semantic models because most of the workforce probably doesn’t understand what they are, or doesn’t recognize them by name. But the findings in our recent Analytics and Data Benchmark Research have changed my mind. The research shows how important a semantic model can be to the success of data and analytics processes. Organizations that have successfully implemented a semantic model are more than twice as likely to report satisfaction with analytics (77%)...
Read More
Topics:
Business Intelligence,
Data Management,
data operations,
Analytics & Data,
semantic model,
AI and Machine Learning
Artificial intelligence using machine learning has passed through the bright, shiny object stage and software vendors are well into the process of making the concept a reality in their offerings. Ventana Research defines AI as the use of technology to process information in much the way humans do, including improving accuracy in recommendations, actions and conclusions as more data is received. I like the alternative term “augmented intelligence” because it emphasizes that these systems enhance...
Read More
Topics:
Planning,
Machine Learning,
Budgeting,
Business Planning,
Financial Performance Management,
forecasting,
digital finance,
profitability management,
AI and Machine Learning
I recently wrote about the potential benefits of data mesh. As I noted, data mesh is not a product that can be acquired, or even a technical architecture that can be built. It’s an organizational and cultural approach to data ownership, access and governance. While the concept of data mesh is agnostic to the technology used to implement it, technology is clearly an enabler for data mesh. For many organizations, new technological investment and evolution will be required to facilitate adoption...
Read More
Topics:
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data,
data operations,
data platforms,
Streaming Data & Events,
AI and Machine Learning