what is Tableau Software?

 

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Tableau established in 2003. Its provides all the core features mandatory in a Business Intelligence System. It is user interface is easy and can be ingress even by the non-experts. It allows to drag and drop data so that you can examine it’s the way you want to. Users can easy to connect to data and create dashboards quick. It follows a new resemble to BI so, that you can produce fast analysis and insights from data. It allows to merge data from different sources and use it as input. Which makes it more than 10 times faster than its candidates.

Tableau designed by meet the necessity of anyone who needs to analyze business data. It’s an executive, analyst or manager. It can support a wide range of industries like plan, real estate and lot others. It has spent years of research to install the best practices for the solutions. The Tableau is high featured software. Its includes a shareable dashboard, interactive reports, and expandability

Users can accept share information from anywhere. As it is total accordant with all the mobile platforms and tablets. You can clear view them as you would on a PC. You can strengthen your analysis by add extra layers of data and incorporate many sources of data. It keeps get rank as one of the superior software for offers BI solutions. It is a great option for small and medium enterprises.

 

Tableau Features

The Tableau offers solutions for all categories of industries, departments and data environments. Below are the unique features which qualify tableau manage so many various scenarios

Speed of Analysis:

As it does not need high level of program expertness. Any computer user with ingress to data can start use it to extract value from the data.

 

Self-Reliant: 

The Tableau doesn’t need a complex software setup. The desktop version which is use by most users is easy to install. Its Contains all the characteristic needed to start and intact data analysis

 

Visual Discovery: 

The user traverse and analysis the data by use of visual tools. There is little script done as near done by drag and drop.

Blend Diverse Data Sets: 

The Tableau allows you to mingle different comparative. Semi structured and raw data sources in real time, without exorbitant up front integration. The users don’t need to know the details of how data stored.

Architecture Agnostic:

The Tableau works in all kinds of devices where data flows. The user need not worry about specific hardware or software requirements to use Tableau

Real Time Collaboration:

It’s allow the colleagues to subscribe to your interactive dashboards. So they see the latest data just by refresh their web browser.

Centralized Data:

The tableau server offers a centralized location. To manage the organization’s published data sources. You can delete, change permissions, add tags, and manage schedules in one suited location. It’s easy to schedule extract refreshes and manage them in the data server.

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Future for Tableau software?

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Tableau is one of the best data visualization tools that. It’s smooth and easy to learn. Tableau’s public version is also quite popular. How ever, we do feel that Qlikview, Qliksense gives some real competition to Tableau. At an enterprise level, We can see more demand for Qlikview/Qliksense than Tableau. As of now learning Tableau will definitely add value to your profile. And Qliksense & Tableau are pretty similar in functionality once you get comfortable.

Tableau Future Scope

The future of tableau is hard to predict. But at present tableau is a better help for career. Having knowledge and skills in tableau will make professionals to get successful career.
It is the fast growing BI tool in the market today, though its growth has hampered in last two quarters. It has a big fan club, great community and devoted users, so it will be a leader for time to come for sure.
Tableau is good business intelligence tool, we impressed by looking its big data attachment. There are good amount of work is happening with cutting edge technologies for tableau. So it’s good time to learn this technology and make good career. If you are good in learning then definitely future is going to be bright for you.
There is a lot of scope for Tableau in India, considering that a more startups and SMB’s are coming up in the country. These companies will generate a huge amount of data and then will use data science to analyze all that. Considering that they are not likely to have a lot of employees. They will need tools like Tableau to do the task of visualizing data for them.
Tableau is a tool with drag and drop serviceability. That can help you makes interactive and beautiful reports, graphs, charts and more.
All other data visualization and BI tools that is easy to understand. Its provides desired results, have a lot of scope in India.

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HBase Architecture

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HBase Architecture Introduction

Apache HBase is an open source of NoSQL database. That provides real-time read/writes of access to those large datasets. A non-relational (NoSQL) database that runs on top of HDFS

What is HBase

The HBase scales to handle huge data sets with billions of rows and millions of columns.  It combines data sources that use a wide variety of different structures and schemas. This integrates with Hadoop and works on some other data access engines through YARN.

The HBase is a column-oriented database management system.  It is well suited for sparse data sets. Many big data cases used in the routine. They do not support a structured query language like SQL.  But, they support HBase isn’t a relational data store at all. This application writes in Java much like a typical Mapreduce  application process. This does support writing applications in Avro, REST, and Thrift.

Works on HBase

The HBase system comprises a set of tables. Each table contains rows and columns. But, like a traditional database. Every a table must have an element defined as a Primary Key.  A column represents an attribute of an object.  If the table is storing diagnostic logs from servers in your environment. Where each row might be a load record. A typical column in such a table would be the timestamp of when the log record. Or perhaps the server name where the record originates manner

      The HBase allows for many attributes to group together into as column families. Such that the elements of a column family are all stored together. This is different from of row type relational database. Where all the columns of a given row stored together. With HBase, you must predefine the table schema and specify the column families.  So able to adapt to changing application requirements

       HDFS has a Name Node and slave nodes.  MapReduce has JobTracker and TaskTracker slaves. In HBase, a master node manages the cluster and region servers store portions of the tables.  Some enterprise concerns due to the availability of the NameNode based on HDFs. HBase is also sensitive to the loss of its master node

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Hadoop HDFS Architecture

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HDFS Introduction

HDFS is distributed file system of JAVA application. It is storage of large volumes of data.

The HDFS and YARN from the data management layer of Apache Hadoop. YARN is the architectural center of Hadoop. The resource management framework. They process of data in many ways such as interactive and real time workloads dataset. YARN provides the resource management. HDFS provides the scalable, fault-tolerant, cost efficient storage for big data.

What is HDFS?

The HDFS is a Java based file system that provides scalable and reliable data storage.  It develops to large clusters of commodity servers. HDFS has demonstrated production scalability of up to 200 PB of storage. But a single cluster support to a billion files and blocks. The quality of enterprise data is available in HDFS. YARN enables many data access applications to process it

The HDFS is a scalable, fault tolerant, distributed storage file system. They work on concurrent data access applications based on coordinated by YARN. HDFS will just work under a variety of physical and systemic manner. Both are combined distribute storage and computation across many servers

Works on HDFS

The HDFS cluster is compress to Name Node. They manage of the cluster metadata and Data Nodes are store in the data. Files and directories work on the Name Node by inodes. Inode attribute like permissions, modification and access times, or namespace and disk space quotas

The file content split into large blocks. They each block of the file split is at many Data Nodes. The blocks store on the local file system on the Data Nodes.

The Name node active monitors on the number of replicas of a block. When a replica of a block lost, Data Node is a failure or disk failure. The Name Node creates another replica of the block. They maintain the namespace tree and the mapped of blocks to Data Nodes. Holding the entire namespace image in RAM

The Name Node does not interact with send requests to Data Nodes. It sends instructions to the Data Nodes by replying to heartbeats sent by those Data Nodes. The instructions include command follows

  • replicate blocks to other nodes
  • remove local block replicas
  • re-register and send an immediate block report
  • Shut down the node.  

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What is Mapreduce and How it works?

Hadoop Mapreduce training Hyderabad

Hadoop Mapreduce Training Hyderabad

Mapreduce is the heart of Hadoop. It is a programming model. They associate implementation of process and generate large data sets in a parallel manner.

Mapreduce is a framework for the process of parallelizable. They across large datasets using a large number of computers (nodes). But, referred to as a cluster or a grid manner. Process data stored either in a file system (unstructured) or in a database (structured). It can take advantage of the locality of data, processing it near the place is store to reduce the distance.

How MapReduce Works

 MapReduce job splits into a large data-set into independent chunks of data. They organize them into key, value pairs for parallel process manner. It improves the speed and reliability of the cluster solutions in greater reliability.

The Map function divides into the Input Format and creates a map task for each range in the input. The Job Tracker distributes those tasks to the worker nodes. The output of each map task spilled into a group of key-value pairs for each reducer.

The Reduce function then collects the various results and combines them.  A process of large data is master node needs to solve. Each reducer pulls the relevant partition from the machines. Where the maps executed, and then write its output back into HDFS. Thus, the reduce is able to collect the data from all the maps for the keys and combine them to solve the problem.

Word count

Mapper: It maps input key & value pairs to a set of intermediate key and value pairs.

Reducer: It reduces a set of intermediate values which share a key to a smaller set of values.

 The wordcount MapReduce program, we provide input file of any text file, as input. When the MapReduce program starts in processes it goes through:

Splitting: It splits the each line in the input file into words.

Mapping: It forms a key value pair. Then divides into the word are the key and 1 is the value assigned to each key.

Shuffling: Common key value pairs get grouped to each other.

Reducing: The values of similar keys and values combine together.

SSIS ( Sequel Server Integration Services )

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Introduction to SSIS

SSIS is a tool used for ETL. ETL stands for Extract Transform and Load. These are simple day-to-day words we use in our daily lives. The figure below depicts ETL in real world scenario.

E-Extract Data:

Extract Data from various homogeneous or non-homogeneous source systems. Data could be store in any of the following forms though not limited to them. Flat file, Database, XML, Web queries etc.

T-Transform Data:

The data are coming from various sources. We cannot assume that the data is structure in the same way across all the sources. Thus, we need to transform the data to a common format so that the other transformations done on them. Once we have the data we need to perform various activities like:

 

  • Data cleansing
  • Mandatory check
  • Data type
  • Foreign key constraints
  • Business rules and apply business rules
  • Creation of surrogate keys
  • Sorting the data
  • Aggregating the data
  • Transposing the data
  • Trim the data to remove blanks.

The list can go on as the business requirements get complex day by day. Hence the transformations get complex. While transformations are we need to log the anomalies in data for reporting

L Load Data: 

Once the transformations done and data takes the form as per the rule. We have to load the data to the destination systems. The destinations can also be as varied as the sources. Once the data reaches the destination, it is consume by other systems.

 

SSIS stands for SQL Server Integration Services. Microsoft introduced Business Intelligence Suite, which includes SSIS, SSAS, and SSRS.

Now what’s this Business Intelligence (BI)? Let me take some time to explain that. As the name suggests, it helps Business run across the globe. Its provides the business with data and ways to look into the data and make business decisions to improve

So, how do the 3 products work in the BI world or how are they organized? To start any business analysis we need data. ETL would be use here to get the data from varied sources and put the data to tables or create Cubes for data warehouse. At one point we have the data with us, SSAS comes into picture to arrange the data and store them to cubes. Next, we need to report the data so that it makes sense to the end user. This is where SSRS comes into picture for announce generation.

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The order of SSIS and SSAS could turn, as both can come first. Having showed this, SSIS makes the backbone of this entire domain as all the data is assemble uses SSIS.

 

 

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Why Automation testing:

The complexity of software development process is increase at a rapid pace. In this situation. There must exist bugs in an application due to human errors. The industry now depends on the software, to test their applications with more precise. This software is also known as an Automation tool. It helps the testers to get a better and efficient end product. Hence this tool like QTP and Selenium are in huge demand in the industry. It is at the top of the market as far as automation tool is anxious. The reason is simple It’s Open Source distributed.

Web applications to rule future:

There is no second view about the future of web application development in the industry. There it comes into our mind. Because this is the best tool for web applications till date in the industry.

Selenium for web app testing:

It is designed for the modern web applications run on modern platforms like android, IOS. There is countless tool are accessible in the industry. But, it has a different existence which makes it rule the industry. It is full dedicated for different types of web applications for different purposes. Its test web apps for modern browsers efficient in less time. Selenium can test large size web applications using different methodologies in less time span

Selenium for cross platform:

It requires some basic code knowledge in which the application have to develop. We can develop a common application for both Android and IOS. It can test the application for the accordant in both platforms.  We can’t ignore the future prospective of Android and IOS web apps in the industry. Hence the importance of Selenium as well.

Future of Selenium testing Hyderabad:

Till there is a prospect of expansion for Android and IOS web applications in future. We must find a bright and potential future of Selenium in the industry. No doubt selenium overtakes other tools but you will see. It is only in the world major tool in the history. Because tools get the name changed. But the concept of automating remains similar.

Hadoop History ?

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What is Hadoop?

Big Data Hadoop is an open source, a Java-based programming framework. It support’s storage and the process of large data sets in cluster computing environment. Apache Software Foundation is installing them.

Hadoop History:

Hadoop invented by Doug Cutting. Hadoop is a part of Apache Lucene Project. This is the origin in Apache Nutch (Open source search Engine) project.  Actually, Apache Nutch starts in 2002 for working crawler and search system. But, they do not scale up to billions of pages on the web page.

In 2003 Google implements one of the projects called Google Distributed Filesystem (GFS) . The storage need for the large files generated as a part of the web crawler and index process manner. GFS architecture Nutch has implemented the project called the Nutch Distributed File system (NDFS).

Google implements MapReduce in 2004. Nutch developers had to work on MapReduce in Nutch Project in 2005. Most of the Algorithms had ported to run using MapReduce and NDFS.

Then moved out of Nutch to form an independent subproject of Lucene called Hadoop. At the same time, Doug Cutting join’s Yahoo. This provided a dedicated team and the resources to turn Hadoop into a system that runs at web scale. Hadoop published in February 2008 when Yahoo! announced that its production search index generates in a 10,000-core Hadoop cluster.

Hadoop Version

In January 2008, Hadoop is one of the top-level projects at Apache, confirming frameworks. At that time, many companies like Yahoo!, such as Last.FM, Facebook, and the New York Times.

In April 2008, Hadoop dominates the world record to become the fastest system to sort a terabyte of data.  Hadoop sorted one terabyte in 209 seconds (just under 3½ minutes). It beats the previous year’s winner of 297 seconds.

Many techniques create to the world just as a description through white papers.  In The world, many of people interest with the idea of GFS.  How it would store data is complete. What MapReduce is and how it would process the data stored in GFS.

People had the knowledge of the technique. But, which was just its description but there was no working model or code provided.       Yahoo implements another major search engine technique is HDFS and MapReduce in 2006-07.  Then based on the white papers published by Google. So finally, the HDFS and MapReduce are two core concepts of Hadoop.

Hadoop implements Doug Cutting. People who have some knowledge of Hadoop. It has the yellow elephant for a logo. So there is a doubt in most people’s mind why Doug Cutting has chosen such a name and logo for his project. There is a reason behind it.The elephant is symbolic in the sense that it is a good solution for Big Data.

Actually, Hadoop was name came from the imagination of Doug Cutting’s son. His son gave to his favorite soft toy. Which was a yellow elephant and this is where the name and the logo for the project have confirmed. Thus, this is the brief history behind Hadoop and its name.

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Selenium IDE Commands List

Selenium IDE Commands List-Hyderabad

The over all IDE script creation process classified into Three Steps.

1: Recording

2: Playing back

3: Saving

Step1: Recording

Selenium IDE supports to record user interactions with the browser. Thus the over all recorded actions are termed as Selenium IDE script.

Step2: Playing back

In this step, first we have to verify track stability and success rate. Then we can execute the recorded script in IDE.

Step2: Saving

Once we have recorded a stable script, we may want to save it for future runs and regressions.

Using Common features of Selenium IDE

Setting Execution speed

While testing web applications, we get across several scenarios where an action performed. Thus we must be having knowledge is enough while dealing such scenarios. So avoid failures while playing back these types of test scenarios.

Using Execute this command option

IDE let have executing a single test step within the entire test script. “Execute this command” option can be use at times when we want to debug of a particular test step.

Using Start point

To specify a start point within a test script to allows in IDE. The start point points to the test step from where we wish to start the test script execution. We customize the script to execute from a certain step.

Using Break point

User to specify break points within a test script to allow in IDE. The break points state Selenium IDE where to pause the test script. It can be use when we want to break the execution in small logical steps to execution trends.

Using Find Button

One of the most crucial features of IDE test scripts is to find and locate web elements within a web page. Web elements which have certain respect of thing associated with them. User can for challenging for making to identify a particular web element different. Selenium IDE provides Find button for the address of this issue.

Selenium IDE Commands

Types of Selenium IDE commands

Here three types of Selenium IDE commands. Each of the test steps in Selenium IDE falls extending any of the following categories.

  1. Actions
  2. Accessors
  3. Assertions

Actions

Actions commands are which interact with direct application either altering. Its state or by pouring some test data.

Accessors

Accessor’s commands are which allows user to store certain values to user defined variable. These keep values can be later on used to create assertions and verifications.

Assertion

Assertions are like to Accessors as they can’t interact with the application. Assertions are use to verify the present state of the application with a regard state.

Forms of Assertions:

  1. Assert:This command makes sure that the test executionis end in case of failure.
  2. Verify: This command lets the IDEto supporton with the test script execution even if the verification is fails.
  3. Wait For:This command waits for an exact condition to arrangebefore executing the next test step.

These conditions are like page to be load, element to be present extending

Microsoft ssas architecture

Microsoft SSAS architecture

SSAS architecture:

SSAS can have different types of database. The Data Base has a mining objects as well as OLAP (Online analytic processes). The application connects to the particular Data type and Analysis service.

Analysis Services is name as “<Server Name> or <Instance Name>”.

Parts of SSAS architecture:

  1. Server objects
  2. Database object
  3. Dimension object
  4. Cube objects
  5. Security Role
  6. Server objects

The Server object represents the server. It represents the examples of MS SQL Server Analysis Services.

Server object provides the below specification:

You can get all database at one connection.

The assemblies of collections, roles of collections.

Traces of collection.

It tells the product name.

It tells the product version and edition.

Database Object:

The Database Object is a container. It stores all data objects for Business intelligence project. It has a Data mining structure, dimensions, OLAP cubes.

Database objects work extend to the objects and attributes below criteria’s:

You can access total cubes of a collection.

Access all the dimensions of collections.

We can estimate the size of a database.

The total data source views and data sources, as two collections.

All database permissions and roles as two collections.

SSAS can have different types of database. The Data Base has a mining objects as well as OLAP (Online analytic processes). The application connects to the particular Data type and Analysis service.

Analysis Services is name as “<Server Name> or <Instance Name>”.

Parts of SSAS architecture:

  1. Server objects
  2. Database object
  3. Dimension object
  4. Cube objects
  5. Security Role
  6. Server objects

The Server object represents the server. It represents the examples of MS SQL Server Analysis Services.

Server object provides the below specification:

You can get all database at one connection.

The assemblies of collections, roles of collections.

Traces of collection.

It tells the product name.

Product version and edition.

Database Object:

The Database Object is a container. It stores all data objects for Business intelligence project. It has a Data mining structure, dimensions, OLAP cubes.

Database objects work extend to the objects and attributes below criteria’s:

You can access total cubes of a collection.

Access all the dimensions of collections.

We can estimate the size of a database.

The total data source views and data sources, as two collections.

All database permissions and roles as two collections.

Dimension Object:

A Dimension object is build of basic attributes and hierarchies. The basic information having a type of the dimension and data source, storage mode. It Attributes are describing the actual Data in the dimension.

Cube Object:

Cube object is build of basic attributes and hierarchies, basic information. The basic information has a type of the dimension and data source and storage mode. Attributes describe the actual Data in the dimension. The cube object Measure groups are sets of measures in the cube. It measure group is a collection of measures, that have a common data source view and a common set of dimensions. Cube object measure group is the unit of a process for measures. It Measure groups can process single and then browsed.

Security Role:

SSAS is a security control by using permissions and roles. Roles is also called as a group of users. Users can call members can be remove or add from roles.

The Dimensions object is build of basic attributes and hierarchies. It has basic information. The basic information having a type of the dimension and data source, storage mode. Attributes describe the actual Data in the dimension.

Cube Object:

Cube object is build of basic attributes and hierarchies, basic information. The basic information has a type of the dimension and data source and storage mode. Attributes describe the actual Data in the dimension. The cube object Measure groups are sets of measures in the cube. It measure group is a collection of measures, that have a common data source view and a common set of dimensions. Cube object measure group is the unit of a process for measures. It Measure groups can process single and then browsed.

Security Role:

SSAS is a security control by using permissions and roles. The Roles are nothing but a group of users. Users can call members can be remove or add from roles.

 

My next article about what is the Basic arch structure of SSIS.