Pinup: Alpine Data Labs

Pinup: Alpine Data Labs

Pinup: Alpine Data Labsalpine-data-labs

The amounts of generated structured and multi-structured data are expanding at an extreme pace. Big data which is defined by data volume, variety of data, and velocity of data generation, is considered as an asset for every organization. This data needs to be processed and condensed into more connected forms in order to be useful for decision making. In other words, big data analytic which uses advanced analytic technologies should be utilized to analyse massive amounts of detailed information in order to improve business performance. Advanced analytics is a collection of related analytical techniques and technologies. It helps data analysts to extract knowledge, discover new insights and make predictions. Organizations can use advanced analytics to adjust their plans and strategies to become more competitive, minimize potential risk and make the best decisions in real time.

Nowadays, there are a lot of companies that provide these services. Alpine Data Labs, founded in 2011, is a perfect example of a provider of advanced analytics software on big data and Hadoop. The company’s products are accessible, easy to use, and built for big data. It offers a collaborative analytics solution that is code-free, requires no download and can be accessed by using any browser.

startup-bigdata

The more data you have, the more difficult it can be for data analysts to derive insight from that data. Chorus (a new cloud application which is enabled by Amazon Web Services, Inc) can provide data analysis tools that convert data formats to a common MAP Reduce format for processing large data sets with parallel and distributed algorithms on the cloud. It simplifies the process of building predictive models for big data.

Alpine as a provider an analytic productivity platform, uses Chorus 3 to provide data analysts with the ability to securely store, analyse and share data. Analytic productivity platform help analytics teams to collaborate, explore data, import data, organize workflows, create workspaces and, share knowledge and insights. Hence, it increases the analytics agility of data science team.

Alpine uses Apache Hadoop, an open-source framework, to process large data sets in a distributed environment. In fact, Hadoop’s scalability for big data volumes is impressive. Although it has the ability to manage a very broad range of data types, it usually takes a long time on Hadoop due to the fact that it is natively a batch-based process. Spark, a new technology which sits on top of Hadoop Distributed File System, can solve problems of Hadoop MapReduce. It can outperform Hadoop by 10x in iterative machine learning workloads and allow an efficient, general-purpose programming language to be used interactively to process large datasets. Hence, Alpine adopted this technology to increases the speed of big data analysis.

By Mojgan Afshari

About Mojgan Afshari

Mojgan Afshari is a senior lecturer in the Department of Educational Management, Planning and Policy at the University of Malaya. She earned a Bachelor of Science in Industrial Applied Chemistry from Tehran, Iran. Then, she completed her Master’s degree in Educational Administration. After living in Malaysia for a few years, she pursued her PhD in Educational Administration with a focus on ICT use in education from the University Putra Malaysia.She currently teaches courses in managing change and creativity and statistics in education at the graduate level. Her research areas include teaching and learning with ICT, school technology leadership, Educational leadership, and creativity. She is a member of several professional associations and editor of the Journal of Education. She has written or co-authored articles in the following journals: Journal of Technology, Pedagogy and Education, The Turkish Online Journal of Educational Technology, International Journal of Education and Information Technologies, International Journal of Instruction, International Journal of Learning, European Journal of Social Sciences, Asia Pacific Journal of Cancer Prevention, Life Science Journal, Australian Journal of Basic and Applied Sciences, Scientific Research and Essays.

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