Business intelligence Consultant 2.5/5 (1)

Experts in BI Development.  Specialist Business Intelligence. Landelijk inzetbaar op uw locatie. Hoge klantbeoordelingen. Medior & senior expertise. Uw flexibele ICT schil. Flexibele contracten. Direct geholpen. Vraag nu de beste Freelance BI Consultants aan. Offerte binnen 24 uur.  Maak direct een terug bel afspraak. Zoek je een door de wol geverfde Business Intelligence consultant? Een die 100% onafhankelijk en deskundig is?

Building or use a Business Intelligence team 

BI roadmap, functioneel ontwerp, technische ontwerp

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Junior BI Developer

Ontwikkel, Bouw en testen van BI systemen.

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Support Self Service BI – Business Intelligence

Bewaken en support van Self Service BI, Management KPI reporting, datawarehousing en management information functioneel Beheer BI systemen.

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Senior BI developer

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IT Business Analyst 2.5/5 (2)

Mr Big Data. Europe First Life Long Learning Environment in the new data economy . Questions ? Call Mr Data Today or book direct free appointment in Amsterdam or Brussels. Mr Data Learn & Grow.

What does an Business Analyst do?

The analyst is involved in the design or modification of business systems or IT systems. The analyst interacts with the business stakeholders and subject matter experts in order to understand their problems and needs. The analyst gathers, documents, and analyzes business needs and requirements.

Hire Business Analyst at Mr Data today!

The analyst is involved in the design or modification of business systems or IT systems. The analyst interacts with the business stakeholders and subject matter experts in order to understand their problems and needs. The analyst gathers, documents, and analyzes business needs and requirements.
What skills does a business analyst need?
Core Skills
  • Communication Skills. Business analysts must be good communicators. …
  • Problem-Solving Skills. No project is without problems. …
  • Critical Thinking Skills. …
  • Documentation and Specification Skills. …
  • Analysis Skills. …
  • Visual Modeling. …
  • Facilitation and Elicitation Skills. …
  • Business Analysis Tools.
Data Skills set

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Business Analyst
Business Analyst

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erp system training certification, erp training strategy document, professional certification programs crm 2.5/5 (2)

ERP, CRM Consulting, Training & Certification Courses. … As ERP is a suite of such applications, trainees can choose the right ERP training courses according to their requirements. At Mr Data, we provide training on the best of ERP software systems, including Microsoft AX, Microsoft NAV, SAP, and Oracle EBS. Questions? Call Mr Data Today.

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erp system training certification,
erp training strategy document,
professional certification programs

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What is ERP?

ERP stands for Enterprise Resource Planning Systems Transform, Integrate and Scale Businesses.
When you search for “ERP” on the web, the sheer amount of information that comes up can be overwhelming—not to mention a little confusing. Every website seems to have its own definition of ERP, and one ERP implementation can vary widely from the next. These differences, however, underscore the flexibility that can make ERP such a powerful business tool.

To get a deeper understanding of how ERP solutions can transform your business, it helps to get a better sense of what ERP actually is and how it works. Here’s a brief introduction to ERP and why it seems like everyone’s talking about it. Questions? Call Mr Data Today.


ERP Integrates Processes Across Business Functions

ERP is an acronym for Enterprise Resource Planning, but even its full name doesn’t shed much light on what ERP is or what it does. For that, you need to take a step back and think about all of the various processes that are essential to running a business, including inventory and order management, accounting, human resources, customer relationship management (CRM), and beyond. At its most basic level, ERP software integrates these various functions into one complete system to streamline processes and information across the entire organization.

The central feature of all ERP systems is a shared database that supports multiple functions used by different business units. In practice, this means that employees in different divisions—for example, accounting and sales—can rely on the same information for their specific needs. Accelerate Business Performance using NetSuite Cloud ERP.

ERP Synchronizes Reporting and Automation


ERP software also offers some degree of synchronized reporting and automation. Instead of forcing employees to maintain separate databases and spreadsheets that have to be manually merged to generate reports, some ERP solutions allow staff to pull reports from one system. For instance, with sales orders automatically flowing into the financial system without any manual re-keying, the order management department can process orders more quickly and accurately, and the finance department can close the books faster. Other common ERP features include a portal or dashboard to enable employees to quickly understand the business performance on key metrics.

A Brief History of ERP


The term ERP was coined in 1990 by Gartner, but its roots date to the 1960s. Back then, the concept applied to inventory management and control in the manufacturing sector. Software engineers created programs to monitor inventory, reconcile balances, and report on status. By the 1970s, this had evolved into Material Requirements Planning (MRP) systems for scheduling production processes. Questions? Call Mr Data Today.

In the 1980s, MRP grew to encompass more manufacturing processes, prompting many to call it MRP-II or Manufacturing Resource Planning. By 1990, these systems had expanded beyond inventory control and other operational processes to other back-office functions like accounting and human resources, setting the stage for ERP as we’ve come to know it.

Today, ERP has expanded to encompass business intelligence (BI) while also handling “front-office” functions such as sales force automation (SFA), marketing automation and ecommerce. With these product advancements and the success stories coming out of these systems, companies in a broad range of industries—from wholesale distribution to ecommerce—use ERP solutions.

Moreover, even though the “e” in ERP stands for “enterprise,” high-growth and mid-size companies are now rapidly adopting ERP systems. Software-as-a-Service (SaaS) solutions—also referred to as “cloud computing”—have helped fuel this growth. Cloud-based solutions not only make ERP software more affordable, they also make these systems easier to implement and manage. Perhaps even more importantly, cloud ERP enables real-time reporting and BI, making them even valuable to executives and staff seeking visibility into the business.

As a result, companies of all sizes and a wide range of industries are transitioning to cloud ERP systems. In fact, Forrester predicts that SaaS-based ERP adoption will rise 21 percent annually through 2015.2 When you stop to consider the benefits of ERP, it’s easy to see why it’s become so popular and why its use will continue to grow so rapidly.


The Business Value of ERP

  • At its core, ERP helps employees do their jobs more efficiently by breaking down barriers between business units. More specifically, an ERP solution:
  • Gives a global, real-time view of data that can enable companies to address concerns proactively and drive improvements. Questions? Call Mr Data Today.

Study in Europe


Studying in Europe is a great idea that provides you the opportunity to obtain an education qualification that is recognised across the European Union and European Economic Area (EU and EEA). As an added benefit, usually a degree from Europe is recognised globally.

To undertake your study in Europe gives you the chance to immerse yourself in a multicultural, multinational society due to the close proximity of the neighbouring countries and the free movement afforded to EU nationals between borders.
As part of your study in Europe you are able to do your study in a multitude of leading global languages such as French, German, Spanish, and of course, English, on top of that you have the chance to live and work in a continent which boasts 7 of the top 10 happiest countries in the world!

Customer Service


  • When can I visit our store?
  • When start our Learning & Training Event ?
  • How much cost course material ?

Mister Big Data Customer Service can answer all your questions about Life Long Learning”  professional certification programs events.

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BI Project Plan 2.5/5 (2)

The development of the BI Business Intelligence Project roadmap provides direction to … to the delivery of projects, but also a high standard of BICC reporting strategy, training
Business intelligence Strategy and Roadmap 2018
Business intelligence Strategy and Roadmap 2018

Business intelligence Strategy and Roadmap 2018

Here are 5 steps you can follow when starting your BI journey.
  1. Structure your BI implementation project.
  2. Identify the requirements for your BI platform.
  3. Choose your BI platform.
  4. Implement your BI platform.
  5. Measure the value of your BI solution

Why BI Strategy & Roadmap?

Business Intelligence (BI) is a way of exploring data to improve business performance, whether to drive profitability or manage costs. It is not only technology you implement and then put in maintenance mode. Whether you are implementing Business Intelligence for the first time or expanding an existing implementation, it’s important to be clear about the goals of your deployment.
You maybe implementing BI system as part of an IT effort or as part of a specific line of business initiative. The goals of these two groups can be quite difference and complex. The goals of the two groups can be quite different . The goals may be driven by the following:

a Sales Analytics Improve customer loyalty, manage products prices, increase market share;
b Supply Chain Analytics On-time delivery, low freight costs;
c Finance Analytics Reduce aging of accounts receivable, reduce budget variance, improve profitability   
d HR Analytics Reduce employee turnover provide competitive pay

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Tip 1: Calibrate the role of IT to fit self-service BI requirements

In traditional enterprise BI environments, most users consume the data, applications and visualizations that IT produces. The self-service trend requires business and IT leadership to be more flexible and calibrate the amount of IT involvement to fit what users are trying to do. The main objective for IT should be to adopt an enabler role and help users achieve their goals by guiding them to the right data, advising how they can get the most out of BI tools and helping to scale up applications.

Tip 2: Update governance to embrace self-service BI and analytics

Users seeking new sources for data discovery and analytics don’t like waiting for new data to be incorporated into the existing data warehouse. Big data lakes and cloud-based data sources are growing in part because users need access to a wider variety of data. Unfortunately, these sources are often not adequately governed, much less vetted for quality and consistency. Organizations will need to examine current BI governance strategies and make sure they account for the expanding data environment.

Tip 3: Revise the semantic layer to support self-service interactive reporting

One of the advantages of mature enterprise BI and data warehouse architectures is having a coherent and up-to-date semantic layer, from which self-service BI and analytics can also benefit. However, diverse and distributed self-service technology can make development and maintenance of a semantic layer challenging and complex. Organizations should evaluate their existing enterprise BI and data warehousing semantic layer to ensure it can extend to ad hoc, self-service BI and analytics use cases.

Tip 4: Balance enterprise BI standardization with user agility

When decentralized and not well coordinated, each self-service technology implementation can become its own data silo. Organizations struggle with balancing user agility and BI standardization. TDWI recommends three steps:

  • Provide managed self-service that offers guidance.
  • Create self-service applications that offer standard choices within them.
  • Aim for less obtrusive IT management and governance.

Tip 5: Introduce self-service data prep carefully

Data preparation is a key concern for those trying to balance BI governance and self-service capabilities for users. To avoid the pitfalls of self-service data preparation, TDWI recommends that organizations centrally monitor metadata, integrate data prep with governance and aim for higher levels of repeatability using automation and web-based administration technologies.

Tip 6: Develop an open architecture to match workloads with technologies

Open source and cloud technologies require organizations to take a fresh look at their enterprise BI and data warehousing architectures. It may be time for a hybrid approach. Not all use cases and workloads will need the rigorous governance and structure of a traditional single architecture for enterprise BI and data warehousing. The strategy must have flexibility and openness to take advantage of the potential of new technologies and methods.

Tip 7: Refresh training to fit diverse user needs

Even though BI and analytics tools are becoming easier to use, it is not necessarily straightforward to understand and apply BI and analytics techniques, particularly for nontechnical users. Among other strategies, this report recommends mentoring through BI teams and encourages collaboration and tip sharing to help users learn from each other.

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Data Warehouse Architecture 2.5/5 (1)

Our Data Warehousing & Business Intelligence training helps you learn data warehousing & data mining concepts. The course also offers tutorials on data . Contact Mr Data. data warehouse architecture, data warehouse software, data warehouse design, types of data warehouse, data warehouse concepts, data warehouse tutorial, dwh osrs, data repository vs data warehouse. Questions? Call Mr Data Today.

The datawarehouse was the biggest powerful reporting and BI’s initial wave of succes. A data warehouse extract information from the ERP and aggreates it to allow for fast analysis of fast amounts of data.

DHW Faiures

Some initial data warehouse projects were deemded faiures, costing millions of dollars and producing no meausrable benefits years of effor. Fortunately, industry consultants quick remedied the data warehouse approach, proposing subject-oriented data marts that can be built in smaller times frames.

The Difference Between a Database and a Data Warehouse

Learn the differences between a database and data warehouse – data optimization, data structure, analysis, concurrent users and use cases.

What is a Database?

A database is a collection of information stored in an organized manner. Many enterprises and organizations create and manage databases using a database management system. Special DBMS software can be used create and store product inventory and customer information, for example.

Organizations most often use databases for online transaction processing (OLTP). Database software needs to provide easy access to information and fast querying so that transactions can be carried out efficiently. Databases are often referred to as operational systems, meaning they are used to process day-to-day transactions in an organization. Questions? Call Mr Data Today.

What is a Data Warehouse?

A data warehouse is a system that pulls together data from many different sources within an organization for reporting and analysis. The reports created from complex queries within a data warehouse are used to make business decisions.

Data warehouses are used for online analytical processing (OLAP), which uses complex queries to analyze rather than process transactions.

Data Warehouse vs Database

Data warehouses and databases are both relational data systems, but were built to serve different purposes. A data warehouse is built to store large quantities of historical data and enable fast, complex queries across all the data, typically using Online Analytical Processing (OLAP). A database was built to store current transactions and enable fast access to specific transactions for ongoing business processes, known as Online Transaction Processing (OLTP). Questions? Call Mr Data Today.


A database is optimized to maximize the speed and efficiency with which data is updated (added, modified, or deleted) and enable faster analysis and data access. Response times from databases need to be extremely quick for efficient transaction processing. The most important aspect of a database is that the write operation is recorded in the system. A business that sells products online wouldn’t be in business very long if its database didn’t make a record of every purchase.

A data warehouse, on the other hand, is optimized for reading and aggregating large data sets. Data warehouses can handle complex analytical queries that would use too much of a database system’s resources.

Data Structure

Most databases use a normalized data structure. Data normalization means reorganizing data so that it contains no redundant data, and all related data items are stored together, with related data separated into multiple tables. Normalizing data ensures the database takes up minimal disk space while response times are maximized.

The more normalized your data is, the more complex the queries needed to read the data because a single query combines data from many tables. This puts a huge strain on computing resources.

The data in a data warehouse does not need to be organized for quick transactions. Therefore, data warehouses normally use a denormalized data structure. A denormalized data structure uses fewer tables because it groups data and doesn’t exclude data redundancies. Denormalization offers better performance when reading data for analytical purposes.

Data Timeline

A database processes day-to-day transactions within an organization. Therefore, databases typically don’t contain historical data—current data is all that matters in a normalized relational database. Questions? Call Mr Data Today.

Data warehouses are used for analytical purposes and business reporting. Data warehouses typically store historical data by integrating copies of transaction data from disparate sources. Data warehouses can also use real-time data feeds for reports that use the most current, integrated information.


While databases are normally used for transactional purposes, analytical queries can still be performed on the data. The problem is that the complexity of the data’s normalized organization makes analytical queries difficult to carry out. A skilled developer or analyst will be required to create such analytical queries. The depth of analysis is limited to static one-time reports because databases just give a snapshot overview of data at a specific time.

The structure of data warehouses makes analytical queries much simpler to perform. No advanced knowledge of database applications is required. Analytics in data warehouses is dynamic, meaning it takes into account data that changes over time.

Concurrent Users

An OLTP database supports thousands of concurrent users. Many users must be able to interact with the database simultaneously without it affecting the system’s performance.

Data warehouses support a limited number of concurrent users compared to operational systems. The data warehouse is separated from front-end applications and it relies on complex queries, thus necessitating a limit on how many people can use the system simultaneously.

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Database vs. Data Warehouse Use Cases

Database Use Cases

Database use cases are related to the day-to-day transactional requirements in an organization. Some examples of database applications include:

  • An airline using an online booking system
  • A hospital registering a patient
  • A bank adding an ATM withdrawal transaction to an account
  • A website creating an order for a product it has sold

Data Warehouse Use Cases

Data warehouse use cases focus on providing high-level reporting and analysis that lead to more informed business decisions. Use cases include:

  • Carrying out data mining to gain new insights from the information held in many large databases
  • Conducting market research by analyzing large volumes of data in-depth
  • An online business analyzing user behavior to make business decisions

Questions? Call Mr Data Today.

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CIO Leadership Training 2.5/5 (1)

Mister Big Data Executive Education offers programs that are designed  a list of critical 21st century skills, all agree on four critical areas for development: Collaboration and teamwork. Creativity and imagination. Critical thinking. Problem enhance your leadership skills, build your foundation in general management. Questions? Call Mr Data Today.

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Executive Education Course Overview:

M1: CIO Leadership Training – Agile Organization Design

Becoming an agile organization allows a company to increase speed of execution, better respond and adapt to customer needs, increase productivity

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M2: Business Intelligence Strategy and Roadmap ppt

Business intelligence (BI) is essential for business growth and competitive advantage, yet reaping benefits from BI requires more than


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M3: Evaluation Criteria for Business Intelligence and Analytics Platforms

This document provides business intelligence (BI) and analytics platform evaluators and decision makers with a comprehensive set of criteria …Questions? Call Mr Data Today.


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M4: Executive Dashboard Templates

An Executive Dashboard is a visual representation, such as the image below, that givesexecutives a quick and easy way to view their company’s performance in real-time.


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M5: How To Implement Business Intelligence

Implementing a business intelligence (BI) solution can be a game changer for your organization by providing integrated insight into data from all corners of the


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M6: Key Performance Indicators For Managers

Your Key Performance Indicators (KPIs) should be the essential metrics that … starting point for the development of a performance management system


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M7: Change Management Principles

Open communication and collaboration is a key agile principle – and a key change management principle as well. Questions? Call Mr Data Today.

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