Using information technology to make data useful is as old as the Information Age. The difference today is that the volume and variety of available data has grown enormously. Big data gets almost all of the attention, but there’s also cryptic data. Both are difficult to harness using basic tools and require new technology to help organizations glean actionable information from the large and chaotic mass of data. “Big data” refers to extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially those related to human behavior and interaction. The challenges in dealing with big data include having the computational power that can scale to the processing requirements for the volumes involved; analytical tools to work with the large data sets; and governance necessary to manage the large data sets to ensure that the results of the analysis are accurate and meaningful. But that’s not all organizations have to deal with now. I’ve coined the term “cryptic data” to focus on a different, less well known sort of data challenge that many companies and individuals face.
Topics: Big Data, data science, Planning, Predictive Analytics, Social Media, forecasting, FP&A, Office of Finance, Operational Performance Management (OPM), Budgeting, Connotate, cryptic, equity research, Finance Analytics, Human Capital, Kofax, Statistics, Analytics, Business Analytics, Hadoop, Business Intelligence (BI), Customer Performance Management (CPM), Data, Datawatch, Financial Performance Management (FPM), Kapow, Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), import.io
My colleague Mark Smith and I recently chatted with executives of Tidemark, a company in the early stages of providing business analytics for decision-makers. It has a roster of experienced executive talent and solid financial backing. There’s a strategic link with Workday that reflects a common background at the operational and investor levels. As it gets rolling, Tidemark is targeting large and very companies as customers for its cloud-based system for analyzing data. It can automate alerts and enhance operating visibility, collaboratively assess the potential impacts of decisions and support the process of implementing those decisions.
Topics: Big Data, Data Warehousing, Performance Management, Planning, Predictive Analytics, GRC, Operational Performance Management (OPM), Budgeting, Master Data, Risk Analytics, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Data Governance, Data Integration, Hadoop, In-Memory Computing, Information Management, Mobility, Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Risk, Sales Performance Management (SPM), Workday, Workforce Performance Management (WPM), Financial Performance Management, Integrated Business Planning