Analytics software is used by business analysts and decision-makers to facilitate the generation of insights from data. It encompasses business intelligence and decision intelligence software, including reports and dashboards as well as embedded analytics and the development of intelligent applications infused with the results of analytic processes. Analytics software enables enterprises to improve business outcomes by operating more efficiently, accelerating product development and enhancing...
Read More
Topics:
Analytics,
AI,
Analytics & Data,
Generative AI
The importance of human resources technology in the workplace is growing at a phenomenal pace. While many HR applications like payroll, benefits management and human resource information systems have been perceived as critical, the new sense of criticality is more extensive than ever. HR technology is necessary to power the function of HR, but it also needs to serve as the leading example of how to engage, embrace and include all workers in the workplace experience and community. HR...
Read More
Topics:
Human Capital Management,
employee experience
I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies. As I explained in the 2023 Data Orchestration Buyers Guide, today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.
Read More
Topics:
Analytics,
data operations,
data platforms,
Analytics & Data,
Generative AI,
AI and Machine Learning,
Data Intelligence
As a business application tech analyst, I tend to focus more on B2B than B2C and the differences between the two. So, when it comes to digital commerce, I am interested in the differences from a process or functional point of view and therefore the potential digital commerce application or platform needs required to support B2B commerce. With more B2B enterprises looking to provide access in a timely manner and when and where the customer chooses, digital commerce is a growing part of the...
Read More
Topics:
Digital Commerce,
Revenue Management,
Office of Revenue
I am happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Ventana Research Workforce Management Suites Buyers Guide is the distillation of a year of market and product research by Ventana Research.
Read More
Topics:
Human Capital Management,
Workforce Management
I previously explained how master data management helps provide trust in data, making it one of the most significant aspects of an enterprise’s strategic approach to data management. More recently, I discussed how it has a role to play in accelerating data democratization as part of data intelligence initiatives. Along with data quality, MDM enables organizations to ensure data is accurate, complete and consistent to fulfill operational business objectives. While it is an established and mature...
Read More
Topics:
Product Information Management,
Operations & Supply Chain,
Sustainability Management,
Analytics & Data,
Data Intelligence
Sage Intacct recently held its annual user conference, and while there were plenty of product announcements and roadmap presentations, my focus here is on the artificial intelligence elements. AI–both predictive and generative–is the most important capability and differentiator in software aimed at finance and accounting departments. Ventana Research asserts that by 2027, almost all vendors of ERP software will incorporate AI to reduce workloads, speed processes and decrease errors.
Read More
Topics:
Office of Finance,
Business Planning,
ERP and Continuous Accounting,
digital finance,
Purchasing/Sourcing/Payments,
Consolidate/Close/Report
I recently attended the Salesforce Trailblazer DX event to learn more about Salesforce’s artificial intelligence products and strategy. Fueled by generative AI, awareness and investment in AI seems to be exploding. ISG research shows that enterprises plan to nearly triple the portion of budgets allocated to AI over the next two years. This doesn’t come as a big surprise when you look at the outcomes enterprises are achieving: Of those that have invested in AI, more than 8 in 10 (84%) have had...
Read More
Topics:
AI,
natural language processing,
Generative AI,
Computer Vision,
Model Building and Large Language Models,
Deep Learning,
Machine Learning Operations
Enterprises are increasingly recognizing the need to streamline operations for efficiency, agility and innovation. This has led to various “operations” or “Ops” initiatives, each focusing on a specific aspect of enterprise IT. From software development and data analytics to IT and cloud management, these Ops groups are transforming the way enterprises operate and compete.
Read More
Topics:
Analytics,
Cloud Computing,
Digital Technology,
data operations,
digital finance,
Digital Security,
Observability,
Analytic Operations,
DevOps and Platforms,
ITOps,
CloudOps,
Machine Learning Operations,
MLOps,
SecOps,
ProjectOps,
AIOps,
NetOps,
DevSecOps,
SecFinOps
I wrote recently about the role that data intelligence has in enabling enterprises to facilitate data democratization and the delivery of data as a product. Data intelligence provides a holistic view of how, when, and why data is produced and consumed across an enterprise, and by whom. This information can be used by data teams toensure business users and data analysts are provided with self-service access to data that is pertinent to their roles and requirements. Delivering data as a product...
Read More
Topics:
Analytics,
Data Ops,
data operations,
data platforms,
Analytics & Data,
AI and Machine Learning,
GenAI,
Data Intelligence
Data and analytics have become increasingly important to all aspects of business. The modern data and analytics stack includes many components, which creates challenges for enterprises and software providers alike. As my colleague Matt Aslett points out, a better term might be modern data and analytics smorgasbord. There are arguments for and against using an assortment of tools versus a consolidated platform. For example, purchasing, integrating and deploying a variety of tools can be complex....
Read More
Topics:
Analytics,
AI,
data operations,
Analytics & Data,
Generative AI,
Data Intelligence
The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. As I explained in our recent Data Pipelines Buyers Guide, data pipelines are essential to generating intelligence from data. Healthy data pipelines are...
Read More
Topics:
Analytics,
data operations,
data platforms,
Analytics & Data,
Generative AI,
AI and Machine Learning,
Data Intelligence