Blog

Marketing Analytics Part 1

Marketing Analytics Part 1

Marketing analytics consists of both qualitative and quantitative, structured and unstructured data used to drive strategic decisions in relation to brand and revenue outcomes. Overall goalYou're a marketing analyst and you've been told by the Chief Marketing Officer that recent marketing campaigns have not been as effective as they were expected to be. You need to analyze the data set to understand this problem and propose data-driven solutions.Section 01: Exploratory Data Analysis Are there any null values or outliers? How will you wrangle/handle them?Are there any variables that warrant transformations?Are there any useful variables that you can engineer with the given data?Do…
Read More
Marketing Analytics Part 2

Marketing Analytics Part 2

Are there any useful variables that you can engineer with the given data?Review a list of the feature names below, from which we can engineer:The total number of dependents in the home ('Dependents') can be engineered from the sum of 'Kidhome' and 'Teenhome'The year of becoming a customer ('Year_Customer') can be engineered from 'Dt_Customer'The total amount spent ('TotalMnt') can be engineered from the sum of all features containing the keyword 'Mnt'The total purchases ('TotalPurchases') can be engineered from the sum of all features containing the keyword 'Purchases' The total number of campaigns accepted ('TotalCampaignsAcc') can be engineered from the sum of…
Read More
Marketing Analytics Part 3

Marketing Analytics Part 3

NumStorePurchases VS MntGoldProds MntFishProducts Distribution Campaign 1 Campaign 2 Campaign 3 Campaign 4 Campaign 5 Section 03: Data Visualization Products VS Amount Spent Purchases Conclusion Recall the overall goal: You're a marketing analyst and you've been told by the Chief Marketing Officer that recent marketing campaigns have not been as effective as they were expected to be. You need to analyze the data set to understand this problem and propose data-driven solutions...Summary of actionable findings to improve advertising campaign success:Advertising campaign acceptance is positively correlated with income and negatively correlated with having kids/teensSuggested action: Create two streams of targeted advertising campaigns,…
Read More
Apache Hive Installation Steps on Ubuntu

Apache Hive Installation Steps on Ubuntu

With this tutorial, we will learn the complete process to install Apache Hive 3.1.2 on Ubuntu 20.The Apache Hive  data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive.Steps for Installing Hadoop on UbuntuStep 1 - Create a directory for example $mkdir /home/bigdata/apachehive Step 2 - Move to hadoop directory $cd /home/bigdata/apachehive Step 3 - Download Apache Hive (Link will change with respect to country so please get the download link from…
Read More
Apache Hadoop 3.3.1 Installation Steps on Ubuntu (Part 1)

Apache Hadoop 3.3.1 Installation Steps on Ubuntu (Part 1)

With this tutorial, we will learn the complete process to install Hadoop 3.3.1 on Ubuntu 20.Supported Java VersionsApache Hadoop 3.3 and upper supports Java 8 and Java 11 (runtime only)Please compile Hadoop with Java 8. Compiling Hadoop with Java 11 is not supported:  HADOOP-16795 - Java 11 compile support OPENApache Hadoop from 3.0.x to 3.2.x now supports only Java 8Apache Hadoop from 2.7.x to 2.10.x support both Java 7 and 8Required software for Linux include: Java must be installed. Recommended Java versions are described at HadoopJavaVersions. ssh must be installed and sshd must be running to use the Hadoop scripts that…
Read More
Apache Hadoop 3.3.1 Installation Steps on Ubuntu (Part 2)

Apache Hadoop 3.3.1 Installation Steps on Ubuntu (Part 2)

Use the following property in the respective filesFile: nano etc/hadoop/core-site.xml: <configuration>   <property>     <name>fs.defaultFS</name>     <value>hdfs://localhost:9000</value>   </property> </configuration> File: nano etc/hadoop/hdfs-site.xml <configuration>   <property>     <name>dfs.replication</name>     <value>1</value>   </property> </configuration> File: nano etc/hadoop/mapred-site.xml <configuration>   <property>     <name>mapreduce.framework.name</name>     <value>yarn</value>   </property>   <property>     <name>mapreduce.application.classpath</name>     <value> $HADOOP_MAPRED_HOME/share/hadoop/mapreduce/*:$HADOOP_MAPRED_HOME/share/hadoop/mapreduce/lib/*</value>   </property> </configuration> File: nano etc/hadoop/yarn-site.xml <configuration>   <property>     <name>yarn.nodemanager.aux-services</name>     <value>mapreduce_shuffle</value>   </property>   <property>     <name>yarn.nodemanager.env-whitelist</name>     <value> JAVA_HOME,HADOOP_COMMON_HOME,HADOOP_HDFS_HOME,HADOOP_CONF_DIR,CLASSPATH_PREPEND_DISTCACHE, HADOOP_YARN_HOME,HADOOP_HOME,PATH,LANG,TZ,HADOOP_MAPRED_HOME*</value>   </property> </configuration> Now check that you can ssh to the localhost without…
Read More
Installing Apache Superset on Ubuntu (Linux) Machine

Installing Apache Superset on Ubuntu (Linux) Machine

Installing Superset from Scratch In Ubuntu 20.04 the following command will ensure that the required dependencies are installed: sudo apt-get install build-essential libssl-dev libffi-dev python3-dev python3-pip libsasl2-dev libldap2-dev Python Virtual EnvironmentWe highly recommend installing Superset inside of a virtual environment. pip install virtualenv You can create and activate a virtual environment using: # virtualenv is shipped in Python 3.6+ as venv instead of pyvenv. # See https://docs.python.org/3.6/library/venv.html python3 -m venv venv . venv/bin/activate Installing and Initializing SupersetFirst, start by installing apache-superset: pip install apache-superset Then, you need to initialize the database: superset db upgrade Finish installing by running through the…
Read More
Installing Apache Cassandra on Ubuntu (Linux) Machine

Installing Apache Cassandra on Ubuntu (Linux) Machine

Installing the binary tarball Verify the version of Java installed. For example: Command $ java -version Result openjdk version "1.8.0_222" OpenJDK Runtime Environment (build 1.8.0_222-8u222-b10-1ubuntu1~16.04.1-b10) OpenJDK 64-Bit Server VM (build 25.222-b10, mixed mode) 2. Download the binary tarball from one of the mirrors on the Apache Cassandra Download site. For example, to download Cassandra 4.0.1: $ curl -OL https://dlcdn.apache.org/cassandra/4.0.1/apache-cassandra-4.0.1-bin.tar.gz The mirrors only host the latest versions of each major supported release. To download an earlier version of Cassandra, visit the Apache Archives. OPTIONAL: Verify the integrity of the downloaded tarball using one of the methods here. For example, to verify…
Read More
Installing Java on Ubuntu (Linux) Machine

Installing Java on Ubuntu (Linux) Machine

Steps for Installing JAVA 8 on Ubuntu Step 1 – Install Java 8 on UbuntuThe OpenJDK 8 is available under default Apt repositories. You can simply install Java 8 on an Ubuntu system using the following commands. sudo apt update sudo apt install openjdk-8-jdk -y Step 2 – Verify Java InstallationYou have successfully installed Java 8 on your system. Let’s verify the installed and current active version using the following command. java -version openjdk version "1.8.0_252" OpenJDK Runtime Environment (build 1.8.0_252-8u252-b09-1ubuntu1-b09) OpenJDK 64-Bit Server VM (build 25.252-b09, mixed mode) Step 3 – Setup JAVA_HOME and JRE_HOME VariableAs you have installed…
Read More
Customer Segmentation using Machine Learning in Apache Spark

Customer Segmentation using Machine Learning in Apache Spark

Customer segmentation is the practice of dividing a company's customers into groups that reflect similarities among customers in each group. The goal of segmenting customers is to decide how to relate to customers in each segment in order to maximize the value of each customer to the business. Problem Statement or Business Problem In this project, we will perform one of the most essential applications of machine learning – Customer Segmentation. We will implement customer segmentation in Apache Spark and Scala, whenever you need to find your best customer. Customer Segmentation is one of the most important applications of unsupervised…
Read More