Select Page

DQ RULE BOOKS – Data Management Training

Results Day Sale

50% OFF – ALL MAIN COURSES

DQ RULE BOOKS – Data Management Training

Results Day Sale

50% OFF – ALL MAIN COURSES

After the completion of GCSE’s, A Levels or a Degree the selection of a career and finding job opportunities can be daunting, with employers looking for students that ‘stand out from the crowd’.

DQ Rule Books can help your CV stand out from the crowd by giving you in-depth knowledge in data management.

The Data Management Industry is one of the fastest growing sectors in the world and salaries are growing to reflect this, a Data Management Contractor can earn upwards of £450 per day.

With our Results Day Sale on our tried and tested courses, there is no better time to set yourself on a career in Data Management.

We are offering 50% off a range of courses, from the Full Data Management Training Course to more specific pillars of data management and also role based courses that give you all you need to know to land a role as a Data Governance or Data Quality Analyst.

Our Courses

Data Management Training – Full Course

Aimed at providing our users with a thorough and comprehensive understanding of data management, our Data Management Training Full Course could be exactly what you need to kick start your career in the industry. 

The course begins with a foundation pillar which gives an introduction to what data management is and why it is important. It then goes on to detail what the 5 key areas of data management are and why they are important.  

The course then specifically details each key area of data management in the following pillars; Data Governance, Data Understanding, Data Quality Assessment & Control, Data Improvement & Maintenance and Data Architecture & IT.  

All pillars are split into modules which have clearly distinguishable learning objectives, so users know exactly what they can expect to learn while working through the training. Each module has several learning activities attached to it to aid users learning such as a presentation, related videos, true/false questions, multiple choice questions and interactive exercises.

Data Management Training – Full Course

Aimed at providing our users with a thorough and comprehensive understanding of data management, our Data Management Training Full Course could be exactly what you need to kick start your career in the industry. 

The course begins with a foundation pillar which gives an introduction to what data management is and why it is important. It then goes on to detail what the 5 key areas of data management are and why they are important.  

The course then specifically details each key area of data management in the following pillars; Data Governance, Data Understanding, Data Quality Assessment & Control, Data Improvement & Maintenance and Data Architecture & IT.  

All pillars are split into modules which have clearly distinguishable learning objectives, so users know exactly what they can expect to learn while working through the training. Each module has several learning activities attached to it to aid users learning such as a presentation, related videos, true/false questions, multiple choice questions and interactive exercises.

Foundations of Data Management

This Foundations of Data Management pillar introduces the concept of data management by describing what it is and why it is important for organisations to focus on it. 

They key areas of data management are discussed such as data governance, data understanding, data quality assessment & control, data improvement & maintenance and data architecture & IT.

Each area is then further discussed in more detail explaining what it consists of, along with detailing why the different areas are important in the overall aim of having effective data management.

Foundations of Data Management

This Foundations of Data Management pillar introduces the concept of data management by describing what it is and why it is important for organisations to focus on it. 

They key areas of data management are discussed such as data governance, data understanding, data quality assessment & control, data improvement & maintenance and data architecture & IT.

Each area is then further discussed in more detail explaining what it consists of, along with detailing why the different areas are important in the overall aim of having effective data management.

Data Governance

The Data Governance pillar introduces the fact that data is valuable and should be treated as an asset in its own right. It describes what a critical data element is and how this links to organisational processes. The Pillar also details the different roles that are used in a data governance program and how a data governance program will benefit management.

Going through such topics as Critical Data Elements, Business Processes, Data Management Policy and CDE Data Standards this pillar gives you a comprehensive outlook on all the components of Data Governance and the importance each components has to a business.

Data Governance

The Data Governance pillar introduces the fact that data is valuable and should be treated as an asset in its own right. It describes what a critical data element is and how this links to organisational processes. The Pillar also details the different roles that are used in a data governance program and how a data governance program will benefit management.

Going through such topics as Critical Data Elements, Business Processes, Data Management Policy and CDE Data Standards this pillar gives you a comprehensive outlook on all the components of Data Governance and the importance each components has to a business.

Data Understanding

The Data Understanding pillar aims to do just that, give you an understanding of data. The pillar covers how data can be modelled into databases, how the data is identified by a unique value, a primary key.  

The pillar then builds on this and shows you how data in tables can be linked and relationships found with primary keys and foreign keys and how these composite keys can be created if they are not saved in the database.  

The pillar also covers what data definitions, glossaries and dictionaries are before covering data lineage and the issues and complexities which are contained in a data’s lineage.

Data Understanding

The Data Understanding pillar aims to do just that, give you an understanding of data. The pillar covers how data can be modelled into databases, how the data is identified by a unique value, a primary key.  

The pillar then builds on this and shows you how data in tables can be linked and relationships found with primary keys and foreign keys and how these composite keys can be created if they are not saved in the database.  

The pillar also covers what data definitions, glossaries and dictionaries are before covering data lineage and the issues and complexities which are contained in a data’s lineage.

Data Quality Assessment & Control

This Data Quality Assessment & Control pillar really dives into the data at a granular level. The data will need to be profiled, the pillar details the process that this involves, how errors in the data can be identified and also how to aggregate and report on them. 

How management view these results through dashboards and how basic standardisations and transformations can be used to address issues in the data.

Issue management and how to incentivise the management into taking action against these data quality issues is also visited in this pillar.

Data Quality Assessment & Control

This Data Quality Assessment & Control pillar really dives into the data at a granular level. The data will need to be profiled, the pillar details the process that this involves, how errors in the data can be identified and also how to aggregate and report on them. 

How management view these results through dashboards and how basic standardisations and transformations can be used to address issues in the data.

Issue management and how to incentivise the management into taking action against these data quality issues is also visited in this pillar.

Data Improvement & Maintenance

This pillar details Data Improvement & Maintenance. After data quality assessment has taken place, any errors that have been identified may need to be remediated. 

This will require data, business and root cause analysis to take place to determine where the data can be improved and maintained.

Will the organisation need to correct the legacy data, correct procedures and possibly develop new software, and how to incentivise the management to proceed into remediation and/or procurement is also discussed.

Data Improvement & Maintenance

This pillar details Data Improvement & Maintenance. After data quality assessment has taken place, any errors that have been identified may need to be remediated. 

This will require data, business and root cause analysis to take place to determine where the data can be improved and maintained.

Will the organisation need to correct the legacy data, correct procedures and possibly develop new software, and how to incentivise the management to proceed into remediation and/or procurement is also discussed.

Data Architecture & IT

The Data Architecture & IT pillar explains how data is identified stored and used within an organisation, and how business architecture can complement data architecture. 

Data can be stored and used in different ways; reference data and master data. These are two of the main types of data that can be stored in a data warehouse, the use of master data creates a need for master data management.

Relational and columnar databases structure and the language used to query them are also explained.

Data Architecture & IT

The Data Architecture & IT pillar explains how data is identified stored and used within an organisation, and how business architecture can complement data architecture. 

Data can be stored and used in different ways; reference data and master data. These are two of the main types of data that can be stored in a data warehouse, the use of master data creates a need for master data management.

Relational and columnar databases structure and the language used to query them are also explained.

Data Governance Analyst – Beginner

DQM Training offers a Data Governance Analyst – Beginner course which will help enable users of all levels to grasp a basic understanding of what data governance is and how it affects them in their day to day activities.  

The course starts off by giving an overview of what data management is and why it is important for an organisation to effectively manage the data they hold. Users then learn how data governance is used to improve the organisation’s management of data.  

Users can benefit by getting an understanding of what critical data is and how processes are used by organisations with this data. The course also details how anyone in an organisation can use a business glossary and CDE data standard to easily get a better understanding of what the data held by the organisation is and the processes it is involved in.  

The course also helps users understand what data ownership is and who is responsible and accountable for data. The course then details how a data management policy (DMP) is used in organisations to set out minimum requirements in respect of how data will be managed.  

All of this will help beginners get a clear understanding of what data governance is and how it is used within organisations. 

Data Governance Analyst – Beginner

DQM Training offers a Data Governance Analyst – Beginner course which will help enable users of all levels to grasp a basic understanding of what data governance is and how it affects them in their day to day activities.  

The course starts off by giving an overview of what data management is and why it is important for an organisation to effectively manage the data they hold. Users then learn how data governance is used to improve the organisation’s management of data.  

Users can benefit by getting an understanding of what critical data is and how processes are used by organisations with this data. The course also details how anyone in an organisation can use a business glossary and CDE data standard to easily get a better understanding of what the data held by the organisation is and the processes it is involved in.  

The course also helps users understand what data ownership is and who is responsible and accountable for data. The course then details how a data management policy (DMP) is used in organisations to set out minimum requirements in respect of how data will be managed.  

All of this will help beginners get a clear understanding of what data governance is and how it is used within organisations. 

Data Governance Analyst – Intermediate 

The Data Governance Analyst – Intermediate course describes why it is important for an organisation to identify its critical data and the business processes and benefits gained from doing so. The course goes further to describe how other data is identified such as master and reference data.

It is important to know where all this data is being held within the organisation so the course also describes how organisations use data modelling and models along with data lineage, to better understand where and how their data is kept. The course can help users get a further understanding of how applications such as a business glossary and a CDE data standard are used, by detailing how data dictionaries and definitions are used to enhance the organisation’s understanding of their data.

The course also explains how it is important to have data which is of high quality, by detailing how organisations use data profiling and data quality rules to monitor the data which they hold. All of this will help users get good understanding of why data governance is important and some of the key areas around having effective data governance.

Data Governance Analyst – Intermediate 

The Data Governance Analyst – Intermediate course describes why it is important for an organisation to identify its critical data and the business processes and benefits gained from doing so. The course goes further to describe how other data is identified such as master and reference data.

It is important to know where all this data is being held within the organisation so the course also describes how organisations use data modelling and models along with data lineage, to better understand where and how their data is kept. The course can help users get a further understanding of how applications such as a business glossary and a CDE data standard are used, by detailing how data dictionaries and definitions are used to enhance the organisation’s understanding of their data.

The course also explains how it is important to have data which is of high quality, by detailing how organisations use data profiling and data quality rules to monitor the data which they hold. All of this will help users get good understanding of why data governance is important and some of the key areas around having effective data governance.

Data Governance Analyst – Advanced

DQM Training offers an Data Governance Analyst – Advanced course which can be used to better understand the finer details around how effective data governance can be achieved. The course can be used by anyone who already has a good understanding of what data governance is but want to know what they can do to implement an effective data governance strategy of their own.

The course starts off by introducing what data understanding is and why it is important for an organisation to understand the data it holds. It then follows on by describing what data quality assessment and control is and some of the techniques used by organisations to monitor the quality of the data.The course then expands user knowledge of critical data and business processes by detailing why some critical data and processes will have to be prioritised over others and the techniques of doing so.

The course also describes how practitioners can use data keys, data relationship discovery and data lineage testing to get  an even better standing of where and how their data is kept and how to identify any issues with how it is stored and used. Areas such as business and data architecture are also detailed which help users get a better understanding of how they need to know the full picture around the data to implement effective data governance.

Finally, the course describes how effective data management incentivisation and training can be used to help the whole organisation have a better understanding of the requirements needed for effective data governance.All of this will help advanced users gain the skills needed to implement effective data governance within their own organisations.

 

Data Governance Analyst – Advanced

DQM Training offers an Data Governance Analyst – Advanced course which can be used to better understand the finer details around how effective data governance can be achieved. The course can be used by anyone who already has a good understanding of what data governance is but want to know what they can do to implement an effective data governance strategy of their own.

The course starts off by introducing what data understanding is and why it is important for an organisation to understand the data it holds. It then follows on by describing what data quality assessment and control is and some of the techniques used by organisations to monitor the quality of the data.The course then expands user knowledge of critical data and business processes by detailing why some critical data and processes will have to be prioritised over others and the techniques of doing so.

The course also describes how practitioners can use data keys, data relationship discovery and data lineage testing to get  an even better standing of where and how their data is kept and how to identify any issues with how it is stored and used. Areas such as business and data architecture are also detailed which help users get a better understanding of how they need to know the full picture around the data to implement effective data governance.

Finally, the course describes how effective data management incentivisation and training can be used to help the whole organisation have a better understanding of the requirements needed for effective data governance.All of this will help advanced users gain the skills needed to implement effective data governance within their own organisations.

 

Data Quality Analyst – Beginner

The Data Quality Analyst – Beginner course starts by providing an overview of what data management is and why it is important for an organisation to effectively manage the data they hold. The course then proceeds to explore how data quality assessment & control is used to improve the organisation’s management of data.

Following this we learn what critical data is and how this critical data will be documented in the CDE data standard. We explore why critical data is important, why it is required to be of high quality and how the actions which are needed to maintain this quality will be documented.

The course then goes on to explain some of the common techniques used when trying to improve the quality of data in an organisation. The process of profiling the data to see the level of quality along with the creation of data quality rules to assess the quality of data are some of the areas explained. The course also explains some of the methods used by organisations to fix the quality of poor data which has been identified. Techniques such as data transformations and standardisations along with the use of data quality domains is detailed.

All of this will help users get a clear understanding of what is needed to be a data quality analyst by understanding how poor data quality needs to be identified and fixed.

Data Quality Analyst – Beginner

The Data Quality Analyst – Beginner course starts by providing an overview of what data management is and why it is important for an organisation to effectively manage the data they hold. The course then proceeds to explore how data quality assessment & control is used to improve the organisation’s management of data.

Following this we learn what critical data is and how this critical data will be documented in the CDE data standard. We explore why critical data is important, why it is required to be of high quality and how the actions which are needed to maintain this quality will be documented.

The course then goes on to explain some of the common techniques used when trying to improve the quality of data in an organisation. The process of profiling the data to see the level of quality along with the creation of data quality rules to assess the quality of data are some of the areas explained. The course also explains some of the methods used by organisations to fix the quality of poor data which has been identified. Techniques such as data transformations and standardisations along with the use of data quality domains is detailed.

All of this will help users get a clear understanding of what is needed to be a data quality analyst by understanding how poor data quality needs to be identified and fixed.

Data Quality Analyst – Intermediate

The Data Quality Analyst – Intermediate course starts by giving users a better understanding of the data and processes they would be working with. It explains why it important to identify the organisations critical data and business processes, along with why it is important to prioritise these in terms of importance as these will be the ones focused on when trying to improve the quality of data.

It is important for a data quality analyst to know where all the data they will be working with is being held, so the course describes how organisations use data modelling and models along with data lineage, to better understand where and how their data is kept. This is all important for data sourcing, which is crucial for a data quality analyst to have a good understanding in, as a key area for data quality analysis getting the data from the right areas of the business correctly.

The course also describes how users can use analysis techniques such as data relationship discovery and data dependency analysis to identify any data quality issues that need to be addressed. This all leads on to root cause analysis, which will help users understand the importance of finding and fixing the root cause of the problem to help permanently fix data quality issues.

The course then finishes by detailing how data quality issues management is used for the consistent capture and reporting of data quality issues, and then how data management incentivisation can be used to help the whole organisation work together to achieve better data quality.

Data Quality Analyst – Intermediate

The Data Quality Analyst – Intermediate course starts by giving users a better understanding of the data and processes they would be working with. It explains why it important to identify the organisations critical data and business processes, along with why it is important to prioritise these in terms of importance as these will be the ones focused on when trying to improve the quality of data.

It is important for a data quality analyst to know where all the data they will be working with is being held, so the course describes how organisations use data modelling and models along with data lineage, to better understand where and how their data is kept. This is all important for data sourcing, which is crucial for a data quality analyst to have a good understanding in, as a key area for data quality analysis getting the data from the right areas of the business correctly.

The course also describes how users can use analysis techniques such as data relationship discovery and data dependency analysis to identify any data quality issues that need to be addressed. This all leads on to root cause analysis, which will help users understand the importance of finding and fixing the root cause of the problem to help permanently fix data quality issues.

The course then finishes by detailing how data quality issues management is used for the consistent capture and reporting of data quality issues, and then how data management incentivisation can be used to help the whole organisation work together to achieve better data quality.

Data Quality Analyst – Advanced

The Data Quality Analyst – Advanced course starts off by explaining what data governance and data understanding are and why they are important. The course also helps users understand what data ownership is and who is responsible and accountable for the data they need to fix.  

The course goes into finer details which would be useful for data quality analysts around data understanding such as data keys and how anyone in an organisation can use a business glossary to easily get a better understanding of what the data held by the organisation is and the processes it is involved in.  

The course also details how data quality analysts can use data lineage testing and auditing to find problems with how data is stored and used within the organisation.  

As fixing data quality problems may also require the data quality analyst to recommend, design, implement and monitor quality procedures for use in the data production process, the course details how processes and procedures, process flow documentation, lean methodology, solution design, back book remediation and root cause remediation are used to help fix data quality issues.

Data Quality Analyst – Advanced

The Data Quality Analyst – Advanced course starts off by explaining what data governance and data understanding are and why they are important. The course also helps users understand what data ownership is and who is responsible and accountable for the data they need to fix.  

The course goes into finer details which would be useful for data quality analysts around data understanding such as data keys and how anyone in an organisation can use a business glossary to easily get a better understanding of what the data held by the organisation is and the processes it is involved in.  

The course also details how data quality analysts can use data lineage testing and auditing to find problems with how data is stored and used within the organisation.  

As fixing data quality problems may also require the data quality analyst to recommend, design, implement and monitor quality procedures for use in the data production process, the course details how processes and procedures, process flow documentation, lean methodology, solution design, back book remediation and root cause remediation are used to help fix data quality issues.

UNTIL THE END OF AUGUST ONLY, SIGN UP VIA ANY OF THE LINKS ON THIS WEBPAGE AND RECEIVE A 50% DISCOUNT CODE FOR ONE OF OUR DATA MANAGEMENT TRAINING COURSES OF YOUR CHOICE DELIVERED TO YOUR INBOX. ALL YOU HAVE TO DO IS REGISTER AN EMAIL ADDRESS AND ONE OF OUR TEAM WILL SEND YOU A CODE, ITS A SIMPLE AS THAT! DON’T MISS OUT ON 50% OFF, REGISTER TODAY!

Don't miss out. Sign up to receive a discount code, today!

Day(s)

:

Hour(s)

:

Minute(s)

:

Second(s)