SQL Server 2012 SSRS SSIS SSAS Courses in London, UK

SQL Server 2012 SSIS Course in London, UK

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A Guided Tour of Integration Services

• Understanding Integration Services
• Exploring and Executing an Integration Services Packages in BIDS
• Exploring and Executing a Package Outside of BIDS

Introduction to Control Flow

• Overview of Control Flow in Integration Services
• Elements in Control Flow
• Control Flow Tasks
• Working with Workflow Tasks
• Precedence Constraints

Introduction to Data Flow

• Data Flow Overview
• Data Flow Pipeline
• Data Flow Sources
• Data Flow Destination
• Data Viewers
• Data Transformations

Variables and Configurations

• Understanding Variables
• Using Variables in Control Flow
• Using Variables in Data Flow
• Understanding Property Expressions
• Using Property Expressions
• Understanding Configurations
• Using Configurations
• Using Variables and Configurations between Packages

Error Logging and Handling

• Error Logging and Handling Overview
• Checkpoints
• Package Logging
• Event Handling

Package Deployment

• Overview of Deploying Packages
• Deployment Challenges
• Create a Package Deployment Utility
• The Package Installation Wizard
• Deploy a Package to the File System
• Deploy a Package to SQL Server
• Importing a Package Using Management Studio
• Redeploying Update Packages

Package Management

• Overview of Package Management
• Managing Packages with DTUtil
• Managing Packages with SQL Server Management Studio
• Executing Packages
• Scheduling Packages with SQL Server Agent
• Integrati

SSRS Training in UK

SSRS – Objectives:

• Describe SQL Server Reporting Services and its Components.
• Create a Reporting Services report.
• Enhance a Reporting Service report.
• Create and manipulate data sets.
• Use report models to implement reporting for business users.
• Configure report publishing and execution settings.
• Implementing subscription for reports.
• Implement custom Reporting Services applications.

SSIS Training in UK

SSIS–Objectives:

 • Plan data transfer and staging solutions for an ETL operation.
• Plan an SSIS Solution
 • Design and implement data flows
• Incorporate logging, error handling, and reliability into a package.
 • Optimize an SSIS solution • Deploy and operate an SSIS solution.

Contact
Prasad

Talend Interview Questions

Dear Developers,

After receiving several requests we have finally decided to start writing interview questions that are generally asked in any of the Talend data integration Interview.

First we have to think about what,where,when ???

What is TDI?

What are the versions available?

What is the difference between TDI and TDQ?

What are the difference between open source and licensed tools?

Talend - Merge multiple files into single file with sorting operation.

Loading Fact Table Using Talend

ROWNUM Analytical Function in Talend

SCD-2 Implementations in Talend

Deployment strategies in Talend

Custom Header Footer in Talend

Data Masking Using Talend

How to use Shared DB Connection in Talend

Load all rows from source to target except last 5

Late Arriving Dimension Using Talend

Date Dimension Using Talend

Dynamic Column Ordering Of Source File Using Talend

what is difference between ETL and ELT components of Talend ?

how to deploy talend projects ?

what are types of available version of Talend ?

how to implement versioning for talend jobs ?

what is tMap component ?

what is difference between tMap and tJoin compoents ?

which component is used to sort that data ?

how to perform aggregate operations/functions on data in talend ?

what types of joins are supported by tMap component ?

Big Data EveryWhere!

•Lots of data is being collected and warehoused

–Web data, e-commerce

–purchases at department/

grocery stores

–Bank/Credit Card 

transactions

–Social Network

DWBI Training Info

DWBI SOLUTIONS has experience in teaching a wide variety of technologies ranging from databases to business intelligence. DWBI SOLUTIONS has some of the best instructors in the industry for Data warehousing & Business Intelligence Training.

Classes can be customized or created to meet your needs. We can provide classroom-style instruction at our own facilities or on-site at your location. We can also provide individual hands-on remote mentoring using teleconferencing. We generally use the latest released version of the software for our classes. Instructor-led courses from DWBI SOLUTIONS may be taught at your location, and can be presented to as many as 5 students per class. To find out more, including scheduling and pricing, call us at +91 9561868844 or write to prasad7350@gmail.com.

We offer Scenario-based business intelligence training with hands on experience for different courses for the following technologies:

Business Intelligence & Information Delivery Technologies

· Cognos

· OBIEE

· SSRS

· 1 Key Agile

Relational Database Management Systems

· Oracle

· SQL Server

· mySql

· MS Access

Extract, Transform & Load (ETL) Technologies

· Pentaho

· Informatica

· Oracle Data Integrator

· SSIS

· DataStage

Queries & Answers

Big Data is the Future of Healthcare

What Is Big Data?

A large amount of data becomes “big data” when it meets three criteria: volume, variety and velocity (see Figure

1). Here is a look at all three:

•

Volume: Big data means there is a lot of data — terabytes or even petabytes (1,000 terabytes). This is perhaps the most immediate challenge of big data, as it requires scalable storage and support for complex, distributed queries across multiple data sources. While many organiza•

Cognizant 20-20 Insights

cognizant 20-20 insights | september 2012

cognizant 20-20 insights

2tions already have the basic capacity to store large volumes of data, the challenge is being able to identify, locate, analyze and aggregate specific pieces of data in a vast, partially structured data set.

•

Variety: Big data is an aggregation of many types of data, both structured and unstructured, including multimedia, social media, blogs, Web server logs, financial transactions, GPS and RFID tracking information, audio/video streams and Web content. While standard techniques and technologies exist to deal with large volumes of structured data, it becomes a significant challenge to analyze and process a large amount of highly variable data and turn it into actionable information. But this is also where the potential of big data potential lays, as effective analytics allow you to make better decisions and realize opportunities that would not otherwise exist.

What Big Data Looks Like

Source: “Extracting Value from Chaos,” IDC Universe study, 2011; Mashable.com,

http://mashable.com/2011/06/28/data-infographic/

Figure 1

New information being created in 2011 also includes replicated

information such as shared documents or duplicated DVDs.orTHE WORLD’S INFORMATION IS DOUBLING EVERY TWO YEARS, with a collossal 1.8 zettabytes to be created and replicated in 2011. In terms of sheer volume, 1.8 ZB of data is equivalent to:Storing 1.8 ZB of information would take:57.5 billion 32 GB Apple iPadsWith that many iPads we could build a mountain of iPads that is 25-times higher than Mount FujiMount Fuji 3,776 milesMount iPad 94,400 milesEvery person in the Unites Stated tweeting3 tweets per minute4,320 tweets per day per personfor 26,976 years non-stopit would take one person47 million yearsof 24/7 viewing to watch every movieOver 200 billion HD moviesEach 120 minutes long

cognizant 20-20 insights 3

With big data poised to change the healthcare ecosystem, organizations need to devote time and resources to understanding this phenomenon and realizing the envisioned benefits.

Executive Summary

Big data is already changing the way business decisions are made — and it’s still early in the game. However, because big data exceeds the capacity and capabilities of conventional storage, reporting and analytics systems, it demands new problem-solving approaches. With the convergence of powerful computing, advanced database technologies, wireless data, mobility and social networking, it is now possible to bring together and process big data in many profitable ways.

Big data solutions attempt to cost-effectively solve the challenges of large and fast-growing data volumes and realize its potential analytical value. For instance, trend analytics allow you to figure out what happened, while root cause and predictive analytics enable understanding of why it happened and what is likely to happen in the future. Meanwhile, opportunity and innovative analytics can be applied to identifying opportunities and improving the future.

All healthcare constituents — members, payers, providers, groups, researchers, governments, etc. — will be impacted by big data, which can predict how these players are likely to behave, encourage desirable behavior and minimize less desirable behavior. These applications of big data can be tested, refined and optimized quickly and

inexpensively and will radically change healthcare delivery and research. Leveraging big data will certainly be part of the solution to controlling spiraling healthcare costs.

Simply by witnessing how big data has transformed consumer IT, it is clear that the promise of big data in healthcare is immense (think Google, Facebook and Apple’s Siri, which all rely on processing and transmitting massive amounts of data). While its potential in healthcare has not been fulfilled, the question is not if, but when.

This white paper will define big data, explore the opportunities and challenges it poses for healthcare, and recommend solutions and technologies that will help the healthcare industry take full advantage of this burgeoning trend.

What are the differences between BI & Datawarehouse?

The differentials are:

DW - is a way of storing data and creating information through leveraging data marts. DM's are segments or categories of information and/or data that are grouped together to provide 'information' into that segment or category. DW does not require BI to work. Reporting tools can generate reports from the DW.

BI - is the leveraging of DW to help make business decisions and recommendations. Information and data rules engines are leveraged here to help make these decisions along with statistical analysis tools and data mining tools.