BIG DATA TERMS EVERYONE SHOULD KNOW

75 BIG DATA TERMS EVERYONE SHOULD KNOW Published by  RAMESH DONTHA · JULY 21, 2017 on Dataconomy.com  This article is a continuation of my first article, 25 Big Data terms everyone should know. Since it got such an overwhelmingly positive response, I decided to add an extra 50 terms to the list.  Just to give you a quick recap, I covered the following terms in my first article: Algorithm, Analytics, Descriptive analytics, Prescriptive analytics, Predictive analytics, Batch processing, Cassandra, Cloud computing, Cluster computing, Dark Data, Data Lake, Data mining, Data Scientist, Distributed file system, ETL, Hadoop, In-memory computing, IOT, Machine learning, Mapreduce, NoSQL, R, Spark, Stream processing, Structured Vs. Unstructured Data. Now let’s get on with 50 more big data terms. Apache Software Foundation Read More …

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BIG DATA 101: INTRO TO PROBABILISTIC DATA STRUCTURES

BIG DATA 101: INTRO TO PROBABILISTIC DATA STRUCTURES CHRISTOPHER LOW · APRIL 17, 2017 on Dataconomy.com Oftentimes while analyzing big data we have a need to make checks on pieces of data like number of items in the dataset, number of unique items, and their occurrence frequency. Hash tables or Hash sets are usually employed for this purpose. But when the dataset becomes so enormous that it cannot fit inside the memory all at once, we need to use special kinds of data structures known as Probabilistic Data Structures. Streaming applications usually require data processing in one pass and then incremental updates. Fortunately, probabilistic data structures fit that processing model very well. Such data structures ignore collisions but errors are controlled Read More …

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How to Create the Perfect Data Dashboard

6 Tips to Create the Perfect Data Dashboard Posted in Dashboard Examples  on February 1, 2017 by Ben on cyfe.com Get started with Cyfe now! It’s FREE!   So you’ve taken the plunge and you’re diving into setting up a data dashboard (and hopefully several) to track your business, operations, financial, and/or marketing metrics and KPIs. Your problem now is that you’ve got SO MANY OPTIONS! We understand. In today’s digital world, we’ve got an information overload. We can track almost anything so thinking about adding all of that to a data dashboard is a little overwhelming. The trick is being efficient, targeted, and organized in your dashboards. Let’s dive into 6 tips that we’ve developed to help you report Read More …

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R data wrangling with DPLYR: Tutorial

R data wrangling with DPLYR: Tutorial with 50 samples Published on February 8, 2017 on LinkedIn.com by Michiel Victor Coming from the world of SQL and busy learning R? This is the bridging article. Written by Deepanshu Bhalla It’s a complete tutorial on data wrangling or manipulation with R. This tutorial covers one of the most powerful R package for data wrangling i.e. dplyr. This package was written by the most popular R programmer Hadley Wickham who has written many useful R packages such as ggplot2, tidyr etc. It’s one of the most popular R package as of date. This post includes several examples and tips of how to use dplyr package for cleaning and transforming data. What is dplyr? Read More …

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Data Engineering & Data Science

Infographic: Data Engineering & Data Science Published on February 21, 2017 on LinkedIn.com  by Michiel Victor, Jake Moody If you’re interested in the field of analytics, you’ve probably heard the terms Data Engineering and Data Science, but do you know the difference? Although there has historically been considerable overlap between the two professions, they are each becoming more distinct. DataCamp created an infographic to help you understand the skills and responsibilities of each role. You’ll also get a chance to compare salaries, popular software and tools used by each, and some educational resources to help get you started! Author: Michiel Victor Data Architect | Data Analyst | Data Warehousing | Data Security | Database Performace | SQL | Reporting | Read More …

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Big Data in Startup/SME Environment

Big Data in Startup/SME Environment Published on January 12, 2017 on LinkedIn by Nikunj Thakkar Founder at dataone.io | City Lead, Ahmedabad Chpater, Headstart Network Foundation Last time we spoke about the role of Big Data in Healthcare, and the response to the article has been nothing but phenomenal. This time, we decided to tackle a whole section of the work environment that really links up with the Big Data, giving shape to the Big Data Industry as well as truly utilizing what Big Data has to offer. We are going to discuss the impact of Big Data on the Startups and Small-Medium size Enterprises(SMEs). The increasing focus on Big Data and its potential to influence almost every sector of Read More …

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TEC 2016 Business Intelligence Buyer’s Guide: Big Data Analytics

TEC BUYERS GUIDE TEC 2016 Business Intelligence Buyer’s Guide: Big Data Analytics Written By: Jorge Garcia Date Published: August 25, 2016 on https://www3.technologyevaluation.com    Abstract While there is no general consensus with respect to how big “big data” is, or can be, not many in the business world disagree that managing huge amounts of data represents a challenge for today’s organizations. And as the amount of data organizations need to grapple with is estimated to double every couple of years, the challenge is becoming even greater. Reliable and efficient solutions for analyzing such big data repositories and effective ways of visualizing the newly discovered data can have a real and positive impact on how organizations use data for improving operations, performance, Read More …

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