Achieve end to end transformation for your IT services and infrastructure through a single cloud based platform. ServiceNow IT Service Management (ITSM) lets you consolidate fragmented tools and legacy systems while automating service management processes. It’s simple to configure and fast to deploy, so you can go live quickly with confidence, while scaling to your business needs.
RPA Technology has the capability to rapidly automate Standard Operating Procedures of existing business processes without any changes or intrusion to the server side of the applications used by the Operations team to complete business transactions.
RPA Tool Course Contents
Robotic Process Automation Introduction
Blue Prism’s Robotic Automation
Running a Process
During this Microsoft Business Intelligence [MSBI] training program, you will dive into Designing an ETL Solution Architecture Using Microsoft SQL Server Integration Services and Implementing and Maintaining Microsoft SQL Server Integration Services. In addition, we will extensively cover how to Design an Analysis Solution Architecture Using Microsoft SQL Server Analysis Services and Implement and Maintain Microsoft SQL Server Analysis Services. You will expand your knowledge on MDX Queries and learn how to create complex reports employing expressions, global collections, and conditional formatting using SQL Server Reporting Services. Microsoft Business Intelligence [MSBI] course consists of all real time tasks which arise in day to day activities. Each and every topic is covered with unique case studies. Microsoft Business Intelligence [MSBI] course is divided into 3 modules and totals more than 50 hours of instructor-led training for SQL Server 2014 Business Intelligence.
Experience : 0 – 1 Years
Qualification: BCA/BCS, B.E./B.Tech, M.Sc, MCA/PGDCA, MCM/MCS
Key Skills: Manual Testing, Test cases & Test Case Execution
We are looking for a Junior Test Engineer responsible for server & client side of our service. Your main duties will include creating and maintaining test cases, test scenarios.
Candidate with 6 months to 1 year Manual Testing expertise required.
Expertise in preparing detailed Test cases & Test Case Execution.
Good experience in Designing, Creating and Maintaining test data.
Candidate must have good written and verbal communication skills.
Candidate must have the flair to learn and grow.
Candidate must have good logical thinking.
Should have knowledge on API testing.
Interview Dates : 22, 23, 24 – March – 2018
Walk-In Dates: 20th to 24th March 2018
Timings: between 10 am to 3 pm
Skyblue Aviation Services Private Limited
511, 4th Floor, KTC Illumination, Gafoor Nagar,
Madhapur, Hyderabad – 500 081, Telangana
Immediate Joiners will be preferred.
Location : Hyderabad
Qualification : B.E./B.Tech, M.Tech, MCA/PGDCA, MCM/MCS
SQL Server, Unit Testing,
Kendo UI, Web Services
Interview Dates : 22, 23 – March – 2018
Walk-in Date/ Time: 22nd March – 23rd March , 9 AM onwards
Terminus Global Techsolutions Private Limited
A: 8-2-693/ 2/3/C/5/1, Mithila Nagar, Banjara Hills,
Road No #12, Hyderabad, Telangana – 500 034
Telephone: 040-23399929 M:7095559993
Hadoop consists of the Hadoop Common package, which provides file system and operating system level abstractions, a MapReduce engine (either MapReduce/MR1 or YARN/MR2) and the Hadoop Distributed File System (HDFS). The Hadoop Common package contains the Java ARchive (JAR) files and scripts needed to start Hadoop.
For effective scheduling of work, every Hadoop-compatible file system should provide location awareness – the name of the rack (or, more precisely, of the network switch) where a worker node is. Hadoop applications can use this information to execute code on the node where the data is, and, failing that, on the same rack/switch to reduce backbone traffic. HDFS uses this method when replicating data for data redundancy across multiple racks. This approach reduces the impact of a rack power outage or switch failure; if any of these hardware failures occurs, the data will remain available
Apache Hadoop is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation. It provides a software framework for distributed storage and processing of big data using the MapReduce programming model. Originally designed for computer clusters built from commodity hardware—still the common use—it has also found use on clusters of higher-end hardware.All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common occurrences and should be automatically handled by the framework
ETL systems commonly integrate data from multiple applications (systems), typically developed and supported by different vendors or hosted on separate computer hardware. The separate systems containing the original data are frequently managed and operated by different employees. For example, a cost accounting system may combine data from payroll, sales, and purchasing.
ETL process involves extracting the data from the source system(s). In many cases, this represents the most important aspect of ETL, since extracting data correctly sets the stage for the success of subsequent processes. Most data-warehousing projects combine data from different source systems. Each separate system may also use a different data organization and/or format. Common data-source formats include relational databases, XML, JSON and flat files, but may also include non-relational database structures such as Information Management System (IMS) or other data structures such as Virtual Storage Access Method (VSAM) or Indexed Sequential Access Method (ISAM), or even formats fetched from outside sources by means such as web spidering or screen-scraping. The streaming of the extracted data source and loading on-the-fly to the destination database is another way of performing ETL when no intermediate data storage is required. In general, the extraction phase aims to convert the data into a single format appropriate for transformation processing.
Extract, Transform & Load is a process in Data Warehousing. ETL refers to, “Extraction of data from different applications” developed & supported by different vendors, managed & operated by different persons hosted on different technologies “into Staging tables-Transform data from staging tables by applying a series of rules or functions – which may include Joining and Deduplication of data, filter and sort the data using specific attributes, Transposing data, make business calculations etc – to derive the data for loading into the destination system-Loading the data into the destination system, usually the data warehouse, which could further be used for business intelligence & reporting purposes.