The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function. For example: import numpy as np a = np.array([1,2,3,4,5]) b = np.array([6,7,8,9,10]) result = np.sum([a,b]) print(result) # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array. For example, the mean of a Numpy array of [1,2,3,4,5] would be result = np.mean([1,2,3,4,5]) print(result) #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par
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Beginner's Tutorial on SaS Visual Analytics
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SAS visual analytics is a completely new architecture from SAS. It has the capability to manage large amounts of data and bring it into memory to analyze it, explore it and publish reports.
Although the data amounts are massive — up to 1.1 billion rows of data, the SAS LASR Analytic Server, to use its full name, was designed to be intuitive to users without an advanced degree in computer science.
A report from Simply hired.
All about SAS analytics Server - The SAS Analytic Server begins with an eight-blade server with 96 processor cores, 768 gigabytes memory and 4.8 terabytes (TB) of disk storage.
The upper end of the reference configurations is 96 blades with 1,152 cores, 9.2 TB memory and 57.6 TB of disk storage, enough disk space to store the entire Library of Congress six times.
Where to Learn SAS Visual Analytics
The speed of in-memory architecture offers tremendous benefit. Organisations can explore huge data volumes and get answers to critical questions in near-real time. SAS Visual Analytics offers a double bonus: the speed of in-memory analytics plus self-service eliminates the traditional wait for IT-generated reports.
Businesses today must base decisions on insight gleaned from data, and that process needs to be close to instantaneous.
Despite being user-friendly, the server has been developed to make it easy for IT to manage the data and secure it without sacrificing usability, Guard said. It includes a visual analytics explorer for ad hoc analysis and discovery, he added.
SAS Visual Analytics helps business users to visually explore data on their own. But it goes well beyond traditional query and reporting.
Running on low-cost, industry-standard blade servers, its high-performance in-memory architecture delivers answers in seconds or minutes instead of hours or days.
Where SAS differs
SAS analytics differ from many business intelligence (BI) solutions which simply move data from a SQL database into memory. That does not support regressions or logistics models becase those capabilities are not built into databases.
In banking, analysts may develop hundreds of models a year; with SAS they will be able to do it 10 to 20 times faster. The importance of changing models rapidly is incredibly important in the banking industry.
A demo on SAS visual analytics:
The computerWorld says-SAS also plans to broaden its user base by making its software more appealing beyond computer statisticians and data scientists.
To this end, the company has paired its data exploration software, called SAS Visual Analytics, with its software for developing predictive models, called SAS Visual Statistics.
The pairing can allow non-data scientists, such as line of business analysts and risk managers, to predict future trends based on current data.
How companies will benefit
With SAS Analytic Server companies can solve problems they had never dealt with before because they it offers speed of analysis at a large scale. Users don’t have to analyze samples; they can look at everything.
AS Visual Analytics will let us quickly dig into our big data to uncover opportunities, and in time, to fully exploit them.”The SAS LASR Analytic Server, uses Hadoop (embedded Hadoop Distributed File System) as local storage at the server for fault tolerance.
SAS LASR Analytic Server has been tested on billions of rows of data and is extremely scalable, bypassing the known column limitations of many relational database management systems (RDBMS).
TLV format contains three parts Tag, Length, and value. In a credit card or financial transactions, the TLV protocol supports this format. Below, you will find the ideas to decode TLV data quickly. According to IBM , the tag tells what type of data it is. The length field denotes the length of the value. The value-field denotes the actual value. Structure of TLV. TLV comprises three field values. Tag Length Value How to Decode TLV The EMV labs developed tags which in turn part of EMV protocol. Each tag has an unique meaning. And the Tag and Length together takes 1 to 4 bytes of memory. 1. The Best example for TLV. Below is the way to decode the EMV tag. The first part of the TLV format is TAG. The second part is LENGTH, and finally the VALUE. Syntax of EMV tag: [Tag][Value Length][Value] (ex. " 9F40 05 F000F0A001 ") where, Tag Name = 9F40 Value Length (in bytes) = 05 Value (Hex representation of bytes. Example, "F0" – 1-byte) = F000F0A001 Finally, what is 9F40
In Kafka, the log file's function is to store entries. Here, you can find entries for the producer's incoming messages. You can call these topics. And, topics are divided into partitions.
Here are seven amazing Infosys AWS interview questions for your quick reference. These are also asked in TCS. Infosys and TCS AWS interview questions 1). What is AWS? Amazon Web Services (AWS) provides on-demand computing resources and services in the cloud, with pay-as-you-go pricing. For example, you can run a server on AWS that you can log on to, configure, secure, and run just as you would a server that's sitting in front of you 2). What you can do with AWS? Store public or private data. Host a static website. These websites use client-side technologies (such as HTML, CSS, and JavaScript) to display content that doesn't change frequently. A static website doesn't require server-side technologies (such as PHP and ASP.NET). Host a dynamic website or web app. These websites include classic three-tier applications, with web, application, and database tiers. Support students or online training programs. Process business and scientific data. Handle peak loads. AWS Quest
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