Corporate performance management (CPM) is a platform containing processes and methodologies that provide an integrated approach to business planning, budgeting and forecasting for finance, sales, marketing, operations and HR. Once implemented it links the strategies of an organization to their plans and execution, therefore helping organizations succeed. In other words, CPM helps corporations use proven and tested methods and processes to improve their business management.
Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. Generally speaking, it is the definition of organizational structures, data owners, policies, rules, process, business terms, and metrics for the end-to-end lifecycle of data (collection, storage, use, protection, archiving, and deletion). It encompasses the people, processes, and technologies required to manage and protect data assets.
Data Management Plan (DMP) is a written document that describes the data you expect to acquire or generate during the a project, how you will manage, describe, analyze, and store those data, and what mechanisms you will use at the end of your project to share and preserve your data.
Data Warehousing (DW) is process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting and is intended to perform queries and analysis and often contain large amounts of historical data.
Content collaboration is a process of sharing, distributing and consuming corporate content within a managed and secured enterprise environment to drive productive collaboration of employees and decision-makers in a company. Generally speaking, it refers to when employees can access, share, sync and collaborate on files using any device–both mobile and desktop. This collaboration and exchange of files is essential to daily activities in many organizations.
Business intelligence (BI) refers to a technical infrastructure or tool that collects, stores, and analyzes the data produced by a company's activities. This platform comprises the strategies and technologies used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations. Generally Speaking, BI is a broad term that encompasses data mining, process analysis, performance benchmarking, and descriptive analytics.
Big data is a term that describes large, hard-to-manage volumes of data – both structured and unstructured – that inundate businesses on a day-to-day basis. It's what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves. Generally speaking, it is the data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency. Characteristics of big data include high volume, high velocity and high variety. Sources of data are becoming more complex than those for traditional data because they are being driven by artificial intelligence (AI), mobile devices, social media and the Internet of Things (IoT).
Big data analytics is the use of advanced analytic techniques against very large, diverse big data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes. Big data analytics is the often complex process of examining big data to uncover information, such as hidden patterns, correlations, market trends and customer preferences , that can help organizations make informed business decisions.