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.
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 running independently, data spread across multiple data centers, data governance, etc. In our ongoing benchmark research project, we are researching the ways in which organizations work with big data and the challenges they face.
Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), data lakes, AI and Machine Learning
Why Collaboration Matters in Analytic Processes
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 feature in analytics technologies by now. I had anticipated that three-quarters of analytics vendors would include collaboration capabilities. More than half the vendors I have evaluated support some comments and discussion in their products, only a few have incorporated social recognition and wall posting as part of their collaborative capabilities. So, what impact does a lack of analytics collaboration have on organizations undergoing digital transformation?
Topics: business intelligence, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, collaborative computing
Blockchains Pose Problems of Persistence and Trust
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 managing their identity and greasing the wheels of trade. That noted, those designing and planning to implement commerce-related blockchains must address fundamental issues if blockchain technology is to achieve its potential.
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.
Topics: Office of Finance, business intelligence, Financial Performance Management, ERP and Continuous Accounting, robotic finance, Predictive Planning, AI and Machine Learning, revenue and lease accounting