The vision of American Institute of Big Data Professionals (AIBDP) is to help enterprises to understand, and implement Big Data to solve real world problems. Thus AIBDP is aimed to serve as the premier worldwide alliance for all stakeholders involved in Big Data related efforts. Representative stakeholders include customers (enterprises), technology vendors, academicians, researchers, and individual practitioners. AIBDP will orchestrate events such as conferences and tutorials to assist in showcasing and disseminating best practices, and to provide a networking opportunity for leaders and practitioners in the field.
AIBDP is an independent not-for-profit body, governed by an Executive Board and an Advisory Board consisting of recognized leaders in the field. AIBDP has subcommittees to represent each major business vertical. Each vertical will have a subcommittee and head, reporting into the main board. Each vertical segment will also have corporate representatives.
Levels of Corporate Membership: Platinum, Diamond, Gold, Silver, Bronze
Example corporate members: IBM, Oracle, SAP, Yahoo, Google etc. AIBDP honors individuals who have distinguished themselves in the area of Big Data and related technologies with Achievement Awards.
AIBDP’s goals are E5 - to evangelize, educate, empower, enlighten, and entertain in the context of Big Data strategy and technology.
1. Evangelize
2. Educate
- On business strategy, technology, methodology, business processes and implementation of Big Data solutions & products - Via educational material and forums such as conferences, community meet-ups, special events, webinars, etc.
3. Enlighten
4. Empower
5. Entertain
Big Data. Everyone in the Silicon Valley and beyond has heard of the term. But it’s not just a term. It’s serious stuff. It might consist of little words, but the implications of these words are enormous. Big data is referred to as such because it encompasses collections of data that are so large and intricate that an entirely new set of tools and mental framework are required in order to tackle it. It brings about an entire new set of challenges; from capture to storage to analysis, the information held within big data is often extremely difficult to extract. This is where we come in.
The paradigm has shifted in information world where narrow & focused business missions are more in demand – solutions are expected more like not “one-fit-for-all” but “fit-for-purpose”. Enterprises, both private & public, are required to discover more about their stakeholders’ facts, relationships, indicators, patterns, trends, and pointers which could not probably be discovered before by using traditional databases and processes. This made it necessary to capture & store more data and just not collect. This gave rise to deal with high volumes of data with lots of variety, often collected much faster than the traditional enterprise data. Although not entirely new, Big Data is a phenomenon that has taken prominence with the advent of open source technologies (like Hadoop / MapReduce / Cassandra etc.) to do Massive Parallel Processing using just commodity servers instead of professional grade servers.
Big Data is the new art and science, using Massive Parallel Processing (MPP) technology, of collection, storage, processing, distribution, and analysis of data with any of the attributes – high volume, high velocity, high variety to extract high value and greater accuracy (veracity).