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IT Project Management Certificate

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Welcome at Mr Data. Learn & Grow Platform

New Way of Working?

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a. we are one people

b. Meet the power player of
Mr Data world

c. what is the next right move ?

d. Education is the key.

minimize your documents

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follow client payments

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saved to the cloud

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automate repeating tasks

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e. better future at mr data

f. university vs. Mr data

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G. price list

Get Easy Acces

€49

Per month

  • 5GB Storage
  • Job & Student e-mail
  • Project Offer platform
  • 1 Year Online Support

€79

Per month

  • 10GB Storage
  • Acces 7:00-15:00
  • 20 Domains
  • Lifetime Support
  • Coffee

€129

Per month

  • 100GB Storage
  • 1 Users
  • 50 Domains
  • Lifetime Support

Register IT Software Training

€499

Level 1

30 days Online

  • 5GB Storage
  • Job & Student e-mail
  • Project Offer platform
  • 1 Year Online Support

€799

Level 1

14 days

Classroom & Online

  • 10GB Storage
  • Acces 7:00-15:00
  • 20 Domains
  • Lifetime Support
  • Coffee

€999

14 days IT Proejct Management

Classroom & Online

  • 100GB Storage
  • 1 Users
  • 50 Domains
  • Lifetime Support

Flexible IT Support for B2B

€499

1 day remote support

  • 5GB Storage
  • Job & Student e-mail
  • Project Offer platform
  • 1 Year Online Support

€560

1day inhouse support

  • 10GB Storage
  • Acces 7:00-15:00
  • 20 Domains
  • Lifetime Support
  • Coffee

€600

1 days IT Proejct Manager

  • 100GB Storage
  • 1 Users
  • 50 Domains
  • Lifetime Support

Select Mr. Big Data Project Management Team

€499

1 day remote support

  • 5GB Storage
  • Job & Student e-mail
  • Project Offer platform
  • 1 Year Online Support

€560

1day inhouse support

  • 10GB Storage
  • Acces 7:00-15:00
  • 20 Domains
  • Lifetime Support
  • Coffee

€600

1 days IT Proejct Manager

  • 100GB Storage
  • 1 Users
  • 50 Domains
  • Lifetime Support

f. price list

work on your self

H. What is a table

Example table in HTML

NameDate of BirthPhone
Bob Smith01-05-65555-123-4567
Joe Smith09-10-79555-801-9876
Jane Doe07-20-70555-232-1818

Example of the same data in a list

Name,Date of Birth,Phone
Bob Smith,01-05-65,555-123-4567
Joe Smith, 09-10-79,555-801-9876
Jane Doe,07-20-70,555-232-1818

Tables in a database

In a database, a table consists of columns and rows of data, much like an Excel spreadsheet. It is often referenced by software programs and web pages, to store and retrieve data for users. There are multiple types of databases, but the structure of a table in each database type is mostly the same.

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I. Normalization

Database Normalization is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy(repetition) and undesirable characteristics like Insertion, Update and Deletion Anomalies. It is a multi-step process that puts data into tabular form, removing duplicated data from the relation tables.

Normalization is used for mainly two purposes,

  • Eliminating redundant(useless) data.
  • Ensuring data dependencies make sense i.e data is logically stored.

The video below will give you a good overview of Database Normalization. If you want you can skip the video, as the concept is covered in detail, below the video.


Problems Without Normalization

If a table is not properly normalized and have data redundancy then it will not only eat up extra memory space but will also make it difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anomalies are very frequent if database is not normalized. To understand these anomalies let us take an example of a Student table.

rollnonamebranchhodoffice_tel
401AkonCSEMr. X53337
402BkonCSEMr. X53337
403CkonCSEMr. X53337
404DkonCSEMr. X53337

In the table above, we have data of 4 Computer Sci. students. As we can see, data for the fields branchhod(Head of Department) and office_tel is repeated for the students who are in the same branch in the college, this is Data Redundancy.

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J. What is MS Power BI software

What is Power BI?

Connect to and visualize any data using the unified, scalable platform for self-service and enterprise business intelligence (BI) that’s easy to use and helps you gain deeper data insight.

 Start free 

Bridge the gap between data and decision making

Data made visual

Easily connect to, model, and visualize your data, creating memorable reports personalized with your KPIs and brand. Get fast, AI-powered answers to your business questions—even when asking with conversational language.

 

Insights at scale

Make the most of your big data investments by connecting to all your data sources with the scale to analyze, share, and promote insights across your organization while maintaining data accuracy, consistency, and security.

 

Strategic, actionable decisions

Work together easily on the same data, collaborate on reports, and share insights across popular Microsoft Office applications such as Microsoft Teams and Excel—empowering everyone in your organization to quickly make data-driven decisions that drive strategic actions.

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K. What is SAP ERP SYSTEM?

ERP stands for enterprise resource planning, but what does ERP mean? The simplest way to define ERP is to think about all the core processes needed to run a company: finance, HR, manufacturing, supply chain, services, procurement, and others. At its most basic level, ERP integrates these processes into a single system.

Yet modern ERP systems are anything but basic. They use the latest technologies—such as machine learning and artificial intelligence (AI)—to provide intelligence, visibility, and efficiency across every aspect of a business.

How a modern ERP system works

See how today’s ERP uses digital assistants to help you focus on what matters: AI and machine learning to automate processes and predictive analytics to support real-time decision making.

Six key benefits of ERP

  1. Higher productivity
    Streamline and automate your core business processes to help everyone in your organization do more with fewer resources.
  2. Deeper insights
    Eliminate information silos, gain a single source of truth, and get fast answers to mission-critical business questions.
  3. Accelerated reporting
    Fast-track business and financial reporting and easily share results. Act on insights and improve performance in real time.
  4. Lower risk
    Maximize business visibility and control, ensure compliance with regulatory requirements—and predict and prevent risk.
  5. Simpler IT
    By using integrated ERP applications that share a database, you can simplify IT and give everyone an easier way to work.
  6. Improved agility
    With efficient operations and ready access to real-time data, you can quickly identify and react to new opportunities.

How do ERP systems work?

An ERP system—also called an ERP suite—is made up of different enterprise resource planning applications that talk to each other and share a database.

ERP software
The ERP software system shown here illustrates enterprise resource planning use cases for sourcing and procurement, as well as sales. Typical ERP modules also address finance, manufacturing, and supply chain, among other applications.

Each application (aka ERP module) typically focuses on one business area. You can combine different modules to meet your needs. Finance, human resources, sales, and logistics are popular starting points. There are also modules specific to industries, from manufacturing to retail.

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L. WHAT IS SAP BI BO - Web intelligence ?

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M. SAP BW / BI

Web Intelligence is part of SAP BusinessObjects product suite and is used for analytical and ad hoc reporting to meet an organization’s business requirements. Web Intelligence is a Business Intelligence reporting tool for business users to analyze data in Data Warehouse. It assists business managers in the decision-making process for building future strategies.

Using Web Intelligence, business users can create basic, medium, and complex reports from transactional data in database and by creating Universes using Information Design Tool/UDT. Various SAP and non-SAP data sources can be used to create reports in Web Intelligence. SAP Business Warehouse (BW) system doesn’t require a Universe to connect to Web Intelligence tool.

Web Intelligence tool can work as a client tool of BusinessObjects platform and also as a standalone tool for reporting.

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N. what is OLTP

What is OLTP?

OLTP is an operational system that supports transaction-oriented applications in a 3-tier architecture. It administers the day to day transaction of an organization. OLTP is basically focused on query processing, maintaining data integrity in multi-access environments as well as effectiveness that is measured by the total number of transactions per second. The full form of OLTP is Online Transaction Processing.

In this OLTP tutorial, you will learn:

Characteristics of OLTP

Following are important characteristics of OLTP:

  • OLTP uses transactions that include small amounts of data.
  • Indexed data in the database can be accessed easily.
  • OLTP has a large number of users.
  • It has fast response times
  • Databases are directly accessible to end-users
  • OLTP uses a fully normalized schema for database consistency.
  • The response time of OLTP system is short.
  • It strictly performs only the predefined operations on a small number of records.
  • OLTP stores the records of the last few days or a week.
  • It supports complex data models and tables.

Type of queries that an OLTP system can Process:

OLTP system is an online database changing system. Therefore, it supports database query such as insert, update, and delete information from the database.

POS system for OLTP

Consider a point of sale system of a supermarket, following are the sample queries that this system can process:

  • Retrieving the description of a particular product.
  • Filtering all products related to the supplier.
  • Searching the record of the customer.
  • Listing products having a price less than the expected amount.

Architecture of OLTP

Here is the architecture of OLTP:

OLTP Architecture
  1. Business / Enterprise Strategy: Enterprise strategy deals with the issues that affect the organization as a whole. In OLTP, it is typically developed at a high level within the firm, by the board of directors or the top management
  2. Business Process: OLTP business process is a set of activities and tasks that, once completed, will accomplish an organizational goal.
  3. Customers, Orders, and Products: OLTP database store information about products, orders (transactions), customers (buyers), suppliers (sellers), and employees.
  4. ETL Processes: It separates the data from various RDBMS source systems, then transforms the data (like applying concatenations, calculations, etc.) and loads the processed data into the Data Warehouse system.
  5. Data Mart and Data warehouse: A data mart is a structure/access pattern specific to data warehouse environments. It is used by OLAP to store processed data.
  6. Data Mining, Analytics, and Decision Making: Data stored in the data mart and data warehouse can be used for data mining, analytics, and decision making.

    This data helps you to discover data patterns, analyze raw data, and make analytical decisions for your organization’s growth.

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O. what is OLAP

OLTP and OLAP: a practical comparison

OLTP and OLAP: The two terms look similar but refer to different kinds of systems. Online transaction processing (OLTP) captures, stores, and processes data from transactions in real time. Online analytical processing (OLAP) uses complex queries to analyze aggregated historical data from OLTP systems.

What is OLTP?

An OLTP system captures and maintains transaction data in a database. Each transaction involves individual database records made up of multiple fields or columns. Examples include banking and credit card activity or retail checkout scanning.

In OLTP, the emphasis is on fast processing, because OLTP databases are read, written, and updated frequently. If a transaction fails, built-in system logic ensures data integrity.

What is OLAP?

OLAP applies complex queries to large amounts of historical data, aggregated from OLTP databases and other sources, for data mining, analytics, and business intelligence projects. In OLAP, the emphasis is on response time to these complex queries. Each query involves one or more columns of data aggregated from many rows. Examples include year-over-year financial performance or marketing lead generation trends. OLAP databases and data warehouses give analysts and decision-makers the ability to use custom reporting tools to turn data into information. Query failure in OLAP does not interrupt or delay transaction processing for customers, but it can delay or impact the accuracy of business intelligence insights.

ETL: the force that joins OLTP and OLAP

The data from one or more OLTP databases is ingested into OLAP systems through a process called extract, transform, load (ETL). With an ETL tool, users can collect data from several sources and send it to a destination, such as an OLAP data warehouse, where it is queried by analytics and business intelligence tools for insights.

Try Stitch with your data warehouse and favorite BI tool today

 

OLTP vs. OLAP: side-by-side comparison

OLTP is operational, while OLAP is informational. A glance at the key features of both kinds of processing illustrates their fundamental differences, and how they work together.

 OLTPOLAP
CharacteristicsHandles a large number of small transactionsHandles large volumes of data with complex queries
Query typesSimple standardized queriesComplex queries
OperationsBased on INSERT, UPDATE, DELETE commandsBased on SELECT commands to aggregate data for reporting
Response timeMillisecondsSeconds, minutes, or hours depending on the amount of data to process
DesignIndustry-specific, such as retail, manufacturing, or bankingSubject-specific, such as sales, inventory, or marketing
SourceTransactionsAggregated data from transactions
PurposeControl and run essential business operations in real timePlan, solve problems, support decisions, discover hidden insights
Data updatesShort, fast updates initiated by userData periodically refreshed with scheduled, long-running batch jobs
Space requirementsGenerally small if historical data is archivedGenerally large due to aggregating large datasets
Backup and recoveryRegular backups required to ensure business continuity and meet legal and governance requirementsLost data can be reloaded from OLTP database as needed in lieu of regular backups
ProductivityIncreases productivity of end usersIncreases productivity of business managers, data analysts, and executives
Data viewLists day-to-day business transactionsMulti-dimensional view of enterprise data
User examplesCustomer-facing personnel, clerks, online shoppersKnowledge workers such as data analysts, business analysts, and executives
Database designNormalized databases for efficiencyDenormalized databases for analysis

OLTP provides an immediate record of current business activity, while OLAP generates and validates insights from that data as it’s compiled over time. That historical perspective empowers accurate forecasting, but as with all business intelligence, the insights generated with OLAP are only as good as the data pipeline from which they emanate.

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P. What is ETL

An Introduction to ETL

Why Do We Need ETL?

Traversing the Four Stages of ETL — Pointers to Keep in Mind

Data Extraction and Data Cleaning

Data Source

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Q. what is SAP BW / BI

SAP Business Warehouse (BW) integrates data from different sources, transforms and consolidates the data, does data cleansing, and storing of data as well. It also includes data modeling, administration and staging area.

SAP Business Intelligence (BI) means analyzing and reporting of data from different heterogeneous data sources. It allows you to acquire data from multiple data sources, data staging, which can be further distributed to different BI systems. A SAP Business Intelligence system can work as a target system for data transfer or source system for distribution of data to different BI targets.

This is a simple tutorial that covers the basics of SAP Business Intelligence and how to handle its various other components.

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R. What is BI and an OLAP Cube?

Business Intelligence Cubes

The Data Revolution has come a long way since our original publishing of “What Are Business Intelligence Cubes” back in 2013. The terms “BI,” “analysis,” and “data driven” are nearly commonplace now among business conversations and exchanges. But it’s okay to still ask about the foundation of business intelligence for Microsoft Dynamics NAV, GP, or AX. It is, after all, more important than ever to understand in order stay atop the competitive landscape.

You may be getting your financial statements. You may even be obtaining your warehouse inventory reports. So you may be wondering, “What do these BI ‘cubes’ have to do with the story?” And why do you need to pay attention?

Turns out, it’s a whole lot.

Take a look at this week’s Throwback Thursday article to revisit the still—arguably even more—relevant look at what business intelligence cubes are and why you need them now.

What Are Business Intelligence Cubes?

Most of us use databases in our daily lives, whether we know it or not: ERP systems, SQL databases, CRM systems, and even Excel files that store data as a “database,” so to speak. These databases are wonderful for collecting and storing information, but not always so great at showing that data in a meaningful way when we want to analyze this information in-depth. Why is this, you ask? Because databases are always designed to get data inserted in the most efficient manner, which frequently creates headaches when users try to get interesting data back out.

Messy, Messy Tables

These databases store information in tables, most often in hundreds or thousands of different tables. These tables relate to each other in sometimes esoteric ways (think of an Excel spreadsheet with 60 worksheets and references pointing all over the place). When we want to report on that data in a sales-by-salesperson report, for example, we must understand the relationships between these tables and their dependencies. We take the salesperson’s name from the Salesperson table, the items sold from the Sales Transactions table, the product description from the Product table, and so on until we come up with a report that makes sense.

This process of building reports from multiple tables can be time-consuming and tedious—if not utterly impossible—especially for non-technical staff. Reporting on multiple tables can cause performance issues as well, especially with large data sets. But now we have cubes. Simplified, cubes are sections of data built from tables in your database. They contain calculations and are often grouped around specific business functions; one cube for sales, one for purchasing, another for inventory, and so on, with each cube containing pertinent and useful metrics for that particular area of the business.

High Performance Cubes

Cubes are a tremendous benefit because of the way they are structured: The heavy lifting is already done through pre-calculation. When you want to get answers from your data, instead of searching multiple tables in your database, your request will go straight to the cubes. Your report that used to take five minutes to run now takes just five seconds, and the end users no longer need to bother with how all of the tables need to be joined together.

When organizations start to collect data in multiple databases, the size of the data sets tends to grow exponentially. Running a standard query against large data sets can cause serious performance issues, which not only sacrifice productivity, but can also lead to users abandoning reports altogether. When this happens, important insights are discarded because the business users simply do not have the time for the data to be compiled. The fascinating thing about cubes and the way they are designed is that whether you are looking at yesterday’s sales transactions or sales over the past five years, it takes the same amount of time to run these two reports, which is just a few seconds in most cases. Why? Because of the power of pre-calculating the values.

Increase User Adoption

Are you hoping to roll out business intelligence for your sales force or purchasing department? Cubes are designed to allow non-technical users choose from a number of pre-calculated items to uncover new insights, and adjust tactics and decisions on the fly. Chances are good that these teams will have difficulty joining multiple tables together with a standard report, but with business intelligence cubes, they can just drag and drop the metrics and dimensions that matter to them into their own dashboard. IT teams appreciate cube environments because end users learn to create their own reports, freeing up the technical staff to do, well, technical things.

Ease-of-use is what gets departments and companies on board with business intelligence. In many cases, this kind of wide user adoption starts a data revolution within a company as more and more managers rely on these systems to help them make fact-based decisions. Cubes help regular business users like us take advantage of all the money we’ve spent on data collection and storage. Now we can use the data to run our business more efficiently and effectively without having to enlist or tie up high value resources like developers, specialists, programmers, and the IT department. This is putting the power to make decisive “game changing” decisions back in our own hands at a fraction of the cost of past lengthy, manual, and time consuming processes, if we had access to the data at all.

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S. what is SAP BODS

 

Before we learn SAP BODS, let’s understand

What is ETL?

ETL stands for Extract-Transform-Load, and it is a process of how data is loaded from the target system to the data warehouse. Data is extracted from a database and transformed to match according to the data warehouse schema. After that, it is loaded back to the data warehouse database in the form of dimension and fact tables.

What is SAP BODS?

SAP BODS is an ETL tool by SAP which can extract data from disparate systems, transform them into meaningful information and load them in various kinds of systems.

Full form of SAP BODS is Business Objects Data Services. It is designed to deliver an enterprise-class solution for data integration, data quality, data processing, data profiling, and text data.

In this beginner’s tutorial, you will learn,

History of SAP BODS

Here, are famous landmarks in the history of SAP BODS:

 
  • In 2002, BusinessObjects rebranded the two software products of Acta as BusinessObjects Data Quality tool and BusinessObjects Data Integration tool.
  • Business Objects acquired by SAP in 2007 and both of these products were renamed as SAP BODQ and SAP BODI.
  • In 2008, SAP merged both of these products in a single tool and renamed it as SAP BusinessObjects Data Services (BODS)

SAP BODS Architecture

Here, are some basic components of SAP BODS architecture:

SAP BODS Architecture Diagram

Repository:

A repository is a set of a table which holds user-created and predefined system object, source, target metadata, and transformation rules. It allows you to set up repositories on an open client/server platform. This helps you for sharing metadata with other enterprise tools. Each local repository is connected with one or more job server which runs the job you have created.

Management Console

SAP BOD Data Services Management Console is the web-based application with the following features.

  • Impact and Linear Analysis
  • Administration
  • Auto Documentation
  • Operational Dashboard
  • Data Validation
  • Data Quality Data Reports.

Job server:

The Job Server component helps you to starts the data movement engine. It allows you to integrate data from multiple sources. It helps you to perform complex data transformations and manages transactions and extractions from ERP systems and other sources.

The Data integration Job server tool allows you to move in data in either batch or real-time mode. It delivers high data throughput and scalability. Moreover, while designing a job, you can also run it from the Designer which tells the Job Server to run the job. The Job Server also allows you to get the job from its associated bods repository.

Data Services Designer

The Data services Designer tool offers an easy-to-use graphical user interface that helps you define transformations, data mappings, and control logic.

This component helps you to build applications containing data and workflows. This component also allows you to manage metadata stored in a repository.

Engines:

After SAP BusinessObjects Data Services job are executed, the Job Server starts the engine to perform data extraction, transformation, and movement. The engine uses parallel processing and in-memory data transformation to offer high data connectivity, quality, and scalability.

Access server:

Access server offers real time request-reply message that collects message request routes them to a real-time service and delivers a message reply in a specific duration. The Acess Server queries message and sends them to the next available real-time service across numerous computing resources.

Address Server:

The next component is the Address Server. It offers address validation and corrections. The Address Server must be started before processing data flows which contain the Global address Cleanse or Global Suggestion list transform with the EMEA engine enabled.

Important terms in SAP BODS

Datastore

A Datastore offers a connection to a data source like a database. It is a linking interface between the actual backend database and Data services. Data store also allows data services to import the description of the data source such as metadata.

CMC (Central Management Console)

CMC is a web-based administration tool for BOD. It is a helpful tool to perform some essential functions like repository registration, user management, etc.

Data Integrator Web Administrator

Data Integrator web administrator is also known as DI web admin. It helps you to maintain repositories in Data services. This SAP BOD services included in DI web admin are Meta Repository, Central Repository, job services, and web services.

SAP Data Services Advantages

Here are a few pros of SAP BODS

  • SAP Business Objects offers better profiling because of too many acquisitions of other companies.
  • The learning curve of this ETL tool is quick, and it is easy to use.
  • Offers an easy to UI interface to perform data manipulation tasks.
  • The objects and functions of BODS allow you to perform manipulations and transformation of data very efficiently.
  • There are system-provided objects and functions which you can easily drag and dropped.
  • SAP BODS allows you to implement various data transformations using Data Integrator language
  • SAP BODS helps you to perform complex data transformations for building customized functions.
  • Data Integrator Designer allows you to store real time and batch jobs and new projects in the repository.

Disadvantages of SAP BODS

Here, are few draws backs of using SAP BODS.

  • It is an expensive tool, so the initial purchase cost is very high.
  • Business Objects many need a number of servers and extensive hardware.
  • Business Objects is a developer platform which means organizations that want to use Business Objects will require the support of a highly skilled development team.

Summary

  • SAP BODS is an ETL tool by SAP which can extract data from disparate systems, transform them into meaningful information and load them in various kinds of systems.
  • Full form of SAO BODS is Business Objects Data Services.
  • Repository, Management Console, Designer, Job Server, Access Server, are important components of SAP BODS Architecture
  • SAP Business Objects offers better profiling because of too many acquisitions of other companies.
  • BODS is an expensive tool, so the initial purchase cost is very high

 

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T. What is Business Intelligence and an OLAP Cube?

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Lorem ipsum dolor sit amet, adhuc labores honestatis pro ne. Pri tantas epicuri inciderint te, nibh efficiendi disputationi ex pri. At facer theophrastus eum, has nulla bonorum vituperata at. Eos utroque consequuntur an, case solum his ei.

Lorem ipsum dolor sit amet, adhuc labores honestatis pro ne. Pri tantas epicuri inciderint te, nibh efficiendi disputationi ex pri. At facer theophrastus eum, has nulla bonorum vituperata at. Eos utroque consequuntur an, case solum his ei.

Lorem ipsum dolor sit amet, adhuc labores honestatis pro ne. Pri tantas epicuri inciderint te, nibh efficiendi disputationi ex pri. At facer theophrastus eum, has nulla bonorum vituperata at. Eos utroque consequuntur an, case solum his ei.

Lorem ipsum dolor sit amet, adhuc labores honestatis pro ne. Pri tantas epicuri inciderint te, nibh efficiendi disputationi ex pri. At facer theophrastus eum, has nulla bonorum vituperata at. Eos utroque consequuntur an, case solum his ei.

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U. SAP Hana SQL

SAP HANA Provides following SAP HANA Functions-

  1. Data Type Conversion Function – Data Type conversion function are used to convert one data type to another. Below are list of Data Type Conversion function-

    E.g. CAST, TO_ALPHANUM, TO_BIGINT, TO_BINARY etc.

  2. Date Time Functions – Date Time Function are used to convert Date/ Time in a different format.

    E.g. – ADD_DAYS, ADD_MONTHS, ADD_SECOND, etc.

  3. Fulltext Functions – Fulltext Functions is used for text search.

    E.g. – SCORE etc.

  4. Number Functions – Number Functions take a numeric value, or string with numeric characters, as input and return numeric values.

    E.g. – ABS, ROUND, POWER, etc.

  5. String Functions – String Functions take a string as input, process them and return value according to function.

    E.g. (ASCII, CHAR, CONCAT, etc.)

  6. Window Functions – Window Functions let user divide result set of a query into groups of rows named window partition.

    E.g. RANK (), DENSE_RANK (), ROW_NUMBER (), etc.

  7. Miscellaneous Function- There are some more functions, which are used for the miscellaneous job. E.g. – CONVERT_CURRENCY, CURRENT_SCHEMA, etc.

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V. Project management

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W. Verander management

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X. Business process Management

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Y. Scrum

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Z1. motivation theory

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Z2. Mindmap

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Z3. Conflict handle

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16. Scrum

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17. Conflict handle

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16. SQL

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business analyst

Z3. Conflict handle

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16. Scrum

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What is business Intelligence

SAP Data warehousing

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Data Analytics

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Data visualization options

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Data Analytics

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What is business Intelligence

data inconsistency

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Workflow Optimization is a cross platform message optimization app for all devices. Contact Us

Data Analytics

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