Things you need to know about Big Data

Category: Education

Presentation Description

For many, it's a nebulous term that invokes images of huge server farms humming away. Or perhaps you think of receiving some kind of personalized advertisement from a retailer. But big data is so much deeper and broader than that. Read this post to know more


Presentation Transcript

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Things You Need to Know about Big Data

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Simply put Big Data refers to large data sets that are computationally analysed to reveal patterns and trends relating to a certain aspect of the data. There’s no minimum amount of data needed for it to be categorised as Big Data as long as there’s enough to draw solid conclusions. M-Brain explains the different facets of Big Data through the 8 V’s..

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Big Data is available in an endless number of places and it’s only increasing as time goes on. A simple Google search will enable you to find a data repository for just about everything. A lot of people aren’t aware of just how much data is already available for access and analysis. How Can You Access Big Data

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How you can access and utilise this data can be split into six parts: Data Extraction Before anything happens some data is needed. This can be gained in a number of ways normally via an API call to a company’s web service. Data Storage The main difficulty with Big Data is managing how it will be stored. It all depends on the budget and expertise of the individual responsible for setting up the data storage as most providers will require some programming knowledge to implement.

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Like it or not data sets come in all shapes and sizes. Before you can even think about how the data will be stored you need to make sure it is in a clean and acceptable format. Data Cleaning Data mining is the process of discovering insights within a database. The aim of this is to provide predictions and make decisions based on the data currently held. Data Mining

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Perhaps the most important is the visualisation of the data. This is the part that takes all the work done prior and outputs a visualisation that ideally anyone can understand. This can be done using programming languages such as and d3.js or software such as Tableau. Data Analysis Data Visualisation Once all the data has been collected it needs to be analysed to look for interesting patterns and trends. A good data analyst will spot something out of the ordinary or something that hasn’t been reported by anyone else.

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How Do You Learn More Big Data is a broad subject so learning it all requires knowledge of several areas. Someone looking to work in the field would need an array of certain skills including one or more of the following: A knowledge of a programming language that relates to data analysis namely R Python SAS or SQL A good understanding of Maths and Statistics Experience on how to scrape a webpage Basic Excel skills

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Are there careers related to Big Data With the growing access to Big Data it should come as no surprise that the volume of careers related is on the rise as well. According to the Data Motion a Big Data Engineer would earn an average salary of 150000 a year.

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actual uses of big data 0 8 S I N A I D E S I G N E R S Netflix’s well known Hadoop data processing platform. Cloud architecture is highly scalable and allows Neflix to quickly provision computing resources as its sees the need. Traffic patterns are analysed across device types and localities to help improve the reliability of video streaming and plan for growth.The technology is also used for Netflix’s recommendation engine based on a customer’s viewing habits and stated preferences. Netflix

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WeatherSignal works by repurposing the sensors in Android devices to map atmospheric readings. Handsets such as the Samsun S4 contain a barometer hygrometer humidity ambient thermometer and lightmeter. Obviously the prospect of millions of personal weather stations feeding into one machine that will average out readings is exciting and one that has the potential to improve Habits Weather

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Heart Disease IBM is predicting heart disease with big data. Analysis of electronic health record data could reveal symptoms at earlier stages than previously. IBM uses the Apache Unstructured Information Management Architecture UIMA to extract the known signs and symptoms of heart failure from available text.  With no single strong indicator only weak signals or ‘co- morbidities’ such as hypertension diabetes associated medications ECG and genomic data etc. can be analysed.

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Infectious diseases Again IBM this Venture Beat article looks at a model and data from the World Health Organization. IBM looked at local climate and temperature to find correlations with how malaria spreads. This analysis is used to predict the location of future outbreaks. The Spatio Temporal Epidemiological Modeler STEM is free and open source.

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Doctor performance Crimson is a system that shows variables including complications hospital readmissions and measures of cost. It colour codes signals as to how well a doctor is performing against his or her peers.

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