# Month: January 2022

### Data Structure & Algorithms Interview Questions

In this post we will be providing some questions frequently asked in Interview. Comment their answers below Arrays How do you find the missing number in a given integer array of 1 to 100?How do you find the duplicate number on a given integer array?How do you find the largest and smallest number in an unsorted integer array?How do you find all pairs of an integer array whose sum is equal to a given number?How do you find duplicate numbers in an array if it contains multiple duplicates?How are duplicates removed from a given array in Java? Linked List How…

### Starting Data Pipelines | Fundamentals of Data Engineering

This article includes a comprehensive introduction with step-by-step definitions and code in data pipelines to introduce the basics of data engineering. Data pipelines are widely used in data science and machine learning and are essential in the process of machine learning to integrate data from multiple streams to gain business intelligence for competitive and profitable analysis. What is a Data Pipeline? Data pipeline is a set of rules that motivates and converts data from multiple sources to an area where new values ​​can be obtained. In the simplest way, the pipeline can only extract data from various sources such as…

### What is Dimensionality Reduction? Overview, Objectives, and Popular Techniques

Table of Contents What is Dimensionality ReductionWhy Dimensionality Reduction is ImportantDimensionality Reduction Methods and ApproachesDimensionality Reduction TechniquesDimensionality Reduction Example Learning by machine is not an easy task. Okay, so that's a lesser statement. Artificial Intelligence and machine learning represent a major step in making computers think like humans, but both concepts are challenging to understand. Fortunately, the profit is worth the effort. Today we are dealing with the process of reducing size, analyzing a key component in machine learning. We will cover its meaning, why it is important, how to do it, and give you a related example to illustrate…

### Interpreting ACF and PACF | Time Series

Introduction Autocorrelation analysis is an important step in the Exploratory Data Analysis (EDA) of time series. The autocorrelation analysis helps in detecting hidden patterns and seasonality and in checking for randomness. It is especially important when you intend to use an ARIMA model for forecasting because the autocorrelation analysis helps to identify the AR and MA parameters for the ARIMA model. Overview FundamentalsAuto-Regressive and Moving Average ModelsStationarityAutocorrelation Function and Partial Autocorrelation FunctionOrder of AR, MA, and ARMA ModelExamplesAR(1) ProcessAR(2) ProcessMA(1) ProcessMA(2) ProcessPeriodicalTrendWhite NoiseRandom-WalkConstant🚀 Cheat SheetCase StudyBitcoinEthereumDiscussion on Random-Walk import numpy as np # linear algebra from numpy.random import seed import math import…

### Types of DTP in SAP BW

DTP determines the process of transferring data between two persistent / non-persistent objects within the BI. In this blog we'll be discussing about the types of DTP in SA Starting with SAP NetWeaver 7.0, InfoPackage uploads data from Source System to PSA. DTP decides to upload more data thereafter. Use Uploading data from PSA to InfoProvider (s).Transferring data from one InfoProvider to another within the BI.Distribution of targeted data outside the BI system; e.g. Open HUBs, etc.In the process of transferring data within the BI, Transformation defines the map layout and logical data analysis for targeted data while, Output Mode…