Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our research shows organizations spend more time cleaning and optimizing data for analysis rather than creating insights. On top of that, they are adding more data sources and information systems which in turn introduces more complexity. Our Analytics and Data Benchmark Research shows that organizations face various challenges with analytics and BI. More than one-third of participants (35%) responded that they find it hard to integrate analytics and BI with business processes and connect to multiple data sources. By embedding analytics and BI into business processes and workflows, organizations can enable users to make critical decisions fast, enhancing overall business agility.
Sisense is Sensible for Embedded Analytics and BI
Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI and Machine Learning, Streaming Analytics
Accelerate Closing with a Faster Tax Provision Process
Managing corporate income taxes is a challenge for chief financial officers and their tax department professionals. Tax codes are often complex, so tax accounting as well as the data required for tax provisions and tax compliance are different enough from statutory accounting to create significant workloads for the tax department. The provision for income tax expense and, for public companies, the assembly of information related to tax-related disclosures, can be a factor holding up the completion of the accounting close.
Topics: Office of Finance, Financial Performance Management, digital finance
Organizations are increasingly utilizing cloud object storage as the foundation for analytic initiatives. There are multiple advantages to this approach, not least of which is enabling organizations to keep higher volumes of data relatively inexpensively, increasing the amount of data queried in analytics initiatives. I assert that by 2024, 6 in ten organizations will use cloud-based technology as the primary analytics data platform, making it easier to adopt and scale operations as necessary.
Topics: Teradata, Data Governance, Data Management, Data, data operations, operational data platforms, Analytic Data Platforms, Object storage, Vantage platform
Vena Provides Practical Support for Integrated Business Planning
Vena Solutions offers midsize organizations a platform for financial planning, analysis and reporting as well as software to manage accounting consolidation and close processes. From the start, Vena has designed its applications to meet the needs of midsize organizations, which typically have the same requirements as large enterprises but with significantly fewer resources to acquire, manage and maintain technology. Ventana Research named Vena a Value Index Leader in Adaptability and a Vendor of Merit in its 2022 Value Index on Business Planning.
Topics: Office of Finance, Business Planning, Financial Performance Management, digital finance
In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven enterprise. Our Analytics and Data Benchmark Research shows that more than one-quarter of organizations find it challenging to access data sources and integrate data and analytics in business processes. Vendors such as IBM offer a broad set of analytics tools with self-service capabilities that allows organizations to reduce IT dependencies and enables decision-makers to recognize performance gaps, market trends and new revenue opportunities. Its technology can simplify data access for self-service applications, enabling users to make business decisions informed by insights and take the guesswork out of decision-making.
Topics: embedded analytics, Analytics, Business Intelligence, IBM, IBM Watson, AI and Machine Learning
