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Data & Business Intelligence Job Descriptions

Data Center Manager: Job Description

Technical Expert

Use our template to create a compelling and comprehensive Data Center Manager job description to attract top talent.

The Data Center Manager job is to manage an infrastructure that houses a huge amount of data and applications for various customers who seek security and availability in this type of center.

Also read what are the differences between Big Data and Business Intelligence

Data Center Manager: the Job

Depending on the type of organization, the data center manager is assigned the function of technical and/or business manager of the data center. The Data Center Manager can either work for companies whose main activity is hosting or for a company that has its own data centers.

Technical and operational management of the data center

Firstly, the Data Center Manager is responsible for the administration of the data center. They ensure the correct technical administration of the servers. Therefore, it is important that the IT infrastructure that supports the data (disk space, network) is flawless.

The data center manager must therefore have solid technical skills in systems, networks, and programming languages. They ensure proper security levels are maintained to protect the structure and customer data.

Supervision and leadership

The Data Center Manager is also a supervisor. In fact they are responsible for developing schedules, anticipating hosting capacity extensions to avoid saturation or contention issues, monitoring service providers, and talking with vendors to match needs with existing technical solutions. Serves as the leader of the technical team and the team responsible for the operation of the data center in terms of staff management.

User support and assistance

As a support officer, the Data Center Manager is responsible for communicating with customers whose computing resources are hosted on data center servers. Also manages all documentation related to hosting and operations (technical manuals, user resource site…). And ensures continuous dialogue and regularly interacts with users to understand their requests.

Required skills of the Data Center Manager

General Knowledge

The Data Center Manage has a solid understanding of hardware and software. They must also be comfortable with the various hardware elements that compose the entire system: network, fiber, firewall, etc. In addition, this professional is familiar with machine architectures, systems with various multiprocessors, and networks (TCP/IP). Finally, they must be proficient with scripting languages such as Bash/Python/Perl.

Interpersonal skills

Being a Data Center manager requires maintaining a dialogue with vendors, service providers, and users to best meet the expectations of each of them and those of the data center. Therefore, to be able to manage teams, it is crucial to be good at dealing with people.

Availability and responsiveness

These are the watchwords of a good Data Center Manager. He or she must be able to respond quickly to technical and service problems, which can arise at any time. Being as organized as possible is therefore necessary to prioritize your tasks and be as responsive as possible.

Context

The data center manager usually begins a career as a technician or engineer. After being distinguished for the ability to manage a team, it is possible to advance to the position of Data Center Manager.

Salary

The position of Data Center Manager varies depending on many factors such as the size of the data center, the size of the customer base and the size of the team. It usually requires two years of experience in technical support to access this position.

The average salary is between 450e and 600e. After a few years, he/she may be offered a responsibility in a larger structure. The career of a Data Center Manager can also be oriented towards the pre-sales of hosting services.

Education and Training

In conclusion, for this position, it is necessary to have at least an operations technician or Bac+2 engineer degree. With lower-level experience, you can qualify for the Data Center Manager position.

You can also read : Top 30 data center manager interview questions and answers

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Data & Business Intelligence Job Descriptions

Data Scientist: Job Description

Data Scientist Job
A Data Scientist is an expert in Data Science, whose job is to extract knowledge from data in order to be able to answer the questions he or she is asked.

Use our template to create a compelling and comprehensive Data Scientist job description to attract top talent.

A Data Scientist is an expert in Data Science, whose job is to extract knowledge from data in order to be able to answer the questions he or she is asked.

In this article you will find all you need to know about the job of Data Scientist, the skilled required, education and training, and the salary expectations.

Also discover what are the differences between Big Data and Business Intelligence

Data Scientist: the job

For the past few years, the job of data scientist has become increasingly relevant due to the growing popularity of Big Data. It is one of the most promising career paths in the IT sector.

Nature of the work

The Data Scientist’s job is based on 4 main missions:

  • Identify the needs and problems that the company entrusts to him/her (several possible areas: marketing, HR, customer loyalty, etc.)
  • Define a statistical model that will enable him/her to respond
  • Build the appropriate tools to collect the data
  • Collect and organize the data to exploit the results. The data can come from various sources.

Required skills of the Data Scientist

Ability to analyse and synthesise

The Data Scientist must be able to anticipate information needs and constantly seek new sources of information.

Technical skills

The mastery of certain technical skills is essential for the Data Scientist. Indeed, they must master NoSQL databases (MongoDB, Hadoop), R programming language, C programming with the Python language…They must also have a solid foundation in statistics as well as notions of machine learning, which can be a real asset.

Curiosity and open-mindedness

To work in this profession, you must also be able to detect the most interesting data. In addition, a passion for information processing and Big Data issues is obviously a plus.

Context

Two engineers from Facebook first used this term in 2008. Harvard Business Review voted Data Scientist as the “sexiest job of the 21st century”. As a result, in large companies, the job is divided into several sub-categories: the data miner (collects data), the data analyst (administers and creates databases), and the data scientist (interprets the data).

Thus, data scientists can be found in different fields, such as the commercial sector or security.

Salary

Depending on the company, Data Scientists work in several areas such as marketing, information systems or the finance department.

Their salary varies between 500 and 800 euros.

Data Scientist: Training and Education

In conclusion, to embark on a career as a data scientist, you need a minimum of 5 years of higher education, with a master’s degree in statistical analysis or computer programming. Many also have a doctorate (bac +8)

Find a Data Scientist Job
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Data & Business Intelligence Job Descriptions

Data Protection Officer: Job Description

Data Protection Officer Job Description
Data Protection Officer Job Description

Use our template to create a compelling and comprehensive Data Protection Officier job description to attract top talent.

The Data Protection Officer job, better known as DPO, is to protect personal data and information.
The DPO’s main task is to ensure that the use of data collected by the company complies with the regulatory framework.

Also read the difference between Big Data and Business Intelligence

Data Protection Officer: the job

As of 25 May 2018, following the implementation of the Data Protection Regulation (GDPR), many companies and administrations whose activities give rise to some form of personal data management, as well as public bodies, are obliged to appoint a DPO.

But, what are the main tasks of a Data Protection Officer?

Ensuring compliance with personal data legislation

Any company that collects or uses personal data must comply with the law. Whether that data is used internally (for recruitment purposes, for example); or externally for commercial purposes (for an email campaign, for example).

Finding alternative uses for data that comply with the law

In order for the company to be able to maintain its activities, while respecting the law concerning the collection and processing of personal data, it is important that the DPO be able to propose alternatives and adapted structures.

Ensuring compliance with the law within the company

In order to inform the various entities of the company of the challenges represented by the data protection law and the importance of compliance with it, the Data Protection Officer must be able to raise awareness and train the internal teams on this subject.

Required skills of the Data Protection Officer

Computer literacy and legal knowledge

The DPO must be familiar with the regulations on the protection of personal information, the laws on ICT, and the various methods and techniques for protecting this data. They must also have knowledge of cyber security.

Versatility

The DPO must be versatile in dealing with different subjects, whether legal or IT-related. Furthermore, his/her job is cross-functional within a company as he/she has to work with various and varied entities such as the marketing, sales, and HR departments, etc., as well as externally with the company’s partners and suppliers.

Context

As mentioned before, for more and more companies, it is now becoming necessary to have a DPO.
On the one hand, since the law of 25 May 2018, in companies and administrations where the activity gives rise to any kind of management of personal data, as well as public bodies, it is mandatory to have a DPO.
On the other hand, data has become a crucial element in companies. To ensure its security and legal use, companies are also increasingly calling for a DPO profile.

Salary

The DPO’s salary varies between 600-800€.

Data Protection Officer: Training and Education

To become a DPO there are training courses from BAC+3 to BAC+5. They can be undertaken in engineering schools or in university courses. As the profession is relatively new, training courses are not available everywhere, but here are some examples:

  • Paris II Panthéon Assas University Diploma in Data Protection Officer;
  • Master of Management in Data Protection from ISEP;
  • IESIA Master in Information and System Security;
  • DPO/CIL diploma from the University of Franche-Comté.

You can also read : A Complete Guide on Cyberattacks and Cyber Defence 202

Find a Data Protection Officer job with Mindquest
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Data & Business Intelligence Job Descriptions

Big Data Engineer: Job Description

Director of Information Systems: Job Description

Use our template to create a compelling and comprehensive Big Data Engineer job description to attract top talent.

The Big Data engineer job consists of developing, maintaining, testing, and evaluating Big Data solutions. They create large-scale data processing systems. They are also experts in data warehousing solutions and database technologies.

Also read the difference between Big Data and Business Intelligence

Big Data Engineer: the Job

Big Data, or the processing and analysis of massive data, has become a real phenomenon in our hyper-connected societies, where the volume of information exchanged is increasing exponentially. This has led to the emergence of a new high-tech profession: the Big Data engineer.

What kinds of assignments does a Big Data Engineer perform?

Adding value to a company’s data

To do this, the Big Data Engineer needs to analyze hundreds of millions of data using highly specialized software and classify the information collected according to the company’s needs and requirements.

Designing and implementing appropriate architecture and solutions

The Big Data Engineer also designs solutions for processing large volumes of data pipelines, which must be sufficiently secure and readable.

Implementing algorithms and technical tests, and monitoring the results

This professional must also test his/her designs and monitor the results. They must optimize the processing and revise the codes if necessary. Moreover, they must constantly update themselves on the technologies and languages is use.

Required skills of the Big Data Engineer

Excellent technical skills

The Big Data Engineer must have a good command of the technologies used by the company, and of digital data systems. He/she also needs to be proficient in technical English and advanced mathematics. In addition, development skills such as Java or Python are greatly appreciated.

Development Infrastructure skills

This professional must be familiar with frameworks such as Hadoop, Hive, Spark, Storm or Pig. He/she must also know how to use MongoDB or Cassandra tools.

Communication skills

These skills are invaluable for reporting. He/she must also be able to work in a team and often be flexible.

Context

As Big Data is a rapidly expanding sector, companies are increasingly looking for this type of profile. Among them, are all types of structures: startups or large groups in the finance, telecommunications, marketing sectors, etc.

Generally, this professional is integrated into the R&D department, the Data Science division, or within a dedicated Big Data department.

Salary

The average daily rate for a Big Data Engineer is between 500 and 800€.

Big Data Engineer: Training and Education

In conclusion, to become a Big Data Engineer, it is necessary to have a Bac +5 in Computer Engineering School with a Master’s degree in Big Data. It is also possible to qualify for this profession after a Doctorate (Bac +8) with a specialization in statistics.

After a few years of experience, the Big Data engineer can progress to the position of IT Director.

You can also read : What Is a Data Warehouse? , What Is a Database? and Top 10 Big data framework for 2023

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Data & Business Intelligence IT Infrastructure Job Descriptions

Database Administrator: Job description

Database Administrator Job description
Database Administrator Job descriptionin this job description his missions, his skills, his training or his salary.

Use our template to create a compelling and comprehensive Database Administrator job description to attract top talent.

The job of the database administrator is to design, manage and administer database management systems and to ensure the consistency, quality, security, and ongoing accessibility of information.

Data Administrator: the job

The following are the steps a database administrator takes to perform his or her job.

Also read the difference between Big Data and Business Intelligence

Design of databases

After taking into account the client’s specific requirements, particularly concerning the size of the database, the database administrator sets up standards and good practices for the development teams.
In collaboration with the various project stakeholders, he/she defines the database implementation choices. Following this, the administrator defines the database parameters, the security rules, models, and designs the tables and keys.

Administration and maintenance

Once the database has been set up, the administrator must implement the data on the technical support. In terms of administration, this means guaranteeing the availability and quality of the data, administering access authorizations, and dealing with security issues. On the other hand, in terms of maintenance, this means ensuring that the data is updated, backed up, and upgraded. It is also the Database Administrator’s responsibility to guarantee the recovery of data and the restoration of conditions following an incident, as well as the correction of any bugs.

Technological monitoring and control of the database

The role of this professional is also to monitor the evolution of database versions and to carry out tests and validation of their management. He/she will also have to anticipate technical developments with a daily technology watch.

Required skills of the Database Administrator

Technical skills

The Database Administrator is familiar with the main software (Oracle, MySQL, SyBase, SQL Server, etc.), the SQL query language, and security issues. Knowledge of Shell scripts under UNIX, Windows or MVS as well as knowledge of technical English is also essential.

Understanding the environment

For this professional, an understanding of the environment, its development, and its operation is essential. Good knowledge of the activities and of the client enables him/her to anticipate the latter’s needs and also to intervene more effectively when necessary.

Reactive and methodical

Methodical and synthetic are the keywords of the database administrator. As with all freelancers, they are also expected to be open-minded and adaptable.

Context

Since the administrator evolves on different supports: mobile databases, shared databases or datawarehouses, the functions of network architect and database administrator are often confused.

The administrator is a real link between the project managers and engineers and the users of the database in order to better define the needs of each person and the company.
The system administrator is required to work on call. Indeed, the systems operate 24 hours a day and many operations require action outside office hours.

As far as the hierarchical reporting line for the freelance database administrator is concerned, it is most often the mission director or technical director.

Also read IT infrastructure: components, job profile, and best practices

Salary

The average daily rate is between €480 and €550

Career progression

This Database Administrator position requires previous experience but will also allow you to progress. For example:

Database Architect
Expert consultant in database optimization
Storage manager or infrastructure manager

Head of a DBA team
 Chief data officer

Database administrator: Training and education

To conclude, the Database Administrator has a profile with high technical added value. In other words, they may have a background in development with a specialization in databases or a generalist background in systems and networks.

Level bac + 3
License pro specializing in database administration or distributed systems…

Bac + 5 level
 Master’s degree in databases and distributed applications, decisional computing…
Engineering degree with a specialization in database engineering or operation…

You can also read : Why and how to make a technological watch? and 10 Top Database Certifications

Categories
IT Infrastructure Job Descriptions Project Manager

Solution Architect: Job description

Solution Architect: Job description
Solution Architect: Job description

Use our template to create a compelling and comprehensive Solution Architect job description to attract top talent.

The Solution Architect job is to design, explain and implement solutions adapted to the company’s specific problems. He or she also builds complex offerings and advises clients on the transformation of information systems. They must study technical feasibility and risks before proposing solutions.

Learn more about IT infrastructure: components, job profile, and best practices

Solution Architect: the job

In a constantly changing technological environment, companies must ensure that their information systems are updated to meet new requirements. This digital transformation requires thus specific skills and practices to keep the company at the forefront of technology

So, what ae the Solutions Architect’s tasks?

Analyzing the project environment and its challenges

The Solution Architect manages the entire project and takes care of solution costs. He or she also manages the development team.

Define a solution path suitable for the company

Typically, companies have their specific information systems, information context, and integration requirements. The Solutions Architect must therefore ensure to propose a system that meets the company’s expectations.

Respect for constraints

Each solution is built using specific tools and implementations that can generate significant costs. The Solutions Architect must therefore know how to optimize the budget assigned to the project, considering the technological and management constraints.

Required skills of the Solution Architect

Excellent technical knowledge

Like the SAP FICO consultant, the Solutions Architects must have excellent technical knowledge in their field. In order to offer the best possible analysis, the Solutions Architect must know everything about operating systems, database management systems, or network equipment.

Specific skills may be required in portals, CMS, multi-channel, BPM, service architecture (SOA), etc.

Analytical skills and a systemic vision of information systems

Designing a solution requires knowledge of the articulation of the different components of the company. The Solutions Architect must therefore understand the company’s strategy and its business model in order to assimilate the objectives.

They must also analyze the technological functioning of the company to identify the means to implement to bring the project to a successful conclusion.

A strong ability to present ideas

Communication skills are essential for the Solutions Architect, who will be negotiating with different stakeholders in the business to understand their needs and analyze risks.

This position involves working with IT engineers, business analysts, and project groups. The Solutions Architect must therefore be able to listen, advise and explain.

Also read our article about Project Management, roles, skills and career paths

Context

Whether it is supporting a digital transformation project, finding a solution that fits the business ecosystem, or preventing information system risks, more and more companies are turning to a Solutions Architect.

A well-designed solution helps the team realize a project on time and on budget, and guarantees a concrete answer to a problem.

The Solutions Architect can work as a sector specialist in a large company or as an external consultant, on their own, or for an ESN (digital service company).

Salary

The average daily rate for an Operations Analyst is between €500 and €900, which is similar to the daily rate for a Storage and Backup Engineer.

Training and education

To become a Solutions Architect, the most common training is a 5-year degree in engineering (networks and IT) or a Master’s degree in networks, telecoms, and IT.

To conclude, the job of Solutions Architects is accessible to experienced managers with skills acquired in project management. A minimum of 8 years of professional experience in the IT field is generally required.

You can also read : 11 examples of Information Architecture

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Data & Business Intelligence Job Descriptions

AI expert: Job description

AI expert job description
AI expert job description

Use our template to create a compelling and comprehensive AI Expert job description to attract top talent.

Certainly, artificial intelligence (AI) is already part of our daily lives (personal assistants, smartphones with facial recognition, etc.) and it is becoming increasingly important in the business world, with numerous technological applications (chatbots, maintenance of installations, etc.). In this AI expert job description you will find everything you need to know about the AI expert job, required skills, training, education, and salary expectations.

Need advice on how to start or develop your freelance consulting business in tech or IT? Need to start a new permanent or freelance assignment? Join Mindquest and get support from our team of experts.

AI expert: the job

Technical skills

What is the role of the artificial intelligence expert?

The main task of the Artificial Intelligence (AI) Expert is to design computer programs capable of performing tasks similar to those performed by a human being. Both a researcher and a computer scientist, an AI expert can work in a wide range of fields.

Also, discover Top 5 Strategies to Overcome the AI Talent Gap

Keeping a constant watch

The mission of the artificial intelligence expert is to solve complex problems. Research and analysis are therefore at the heart of the job. The AI expert must possess very advanced computer skills, as his or her expertise is constantly sought in the development of artificial intelligence projects. Since AI is still a relatively new field of expertise, the AI expert must constantly keep abreast of technological developments.

Understanding and analyzing problems

Since the role of the AI expert is to create software that mimics human reasoning, the expert must be able to analyze the human brain in relation to a problem and thus develop intuitive human-machine interfaces.

Developing and designing solutions

The AI expert can work on extremely diverse and varied projects. His or her day-to-day tasks are generally algorithm design, error checking, and programming.

Required skills of the AI expert

AI expert required skills

Strong technical skills

The job of Artificial Intelligence Expert requires advanced technical skills because AI-based applications cross many technologies (web crawling, data mining, data science, machine learning, deep learning, etc.).

Strength of proposal, and ability to listen

As far as soft skills are concerned, the AI Expert must show a strong spirit of initiative, interpersonal skills, and good listening skills. Since these qualities will enable him/her to carry out his/her projects successfully, communicate with all stakeholders, and call on external experts.

Ability to work in a team

To conclude, research in Artificial Intelligence is definitely not a solitary job. In fact, the AI Expert will have to work with various experts and will have to know how to federate these experts and listen to their advice to make progress in his research.

Also discover the differences between Business Intelligence and Big Data

Context

AI expert context

Expertise in Artificial Intelligence is very rare and therefore highly sought after. As a researcher and computer scientist, the AI Expert is highly qualified and can work in different fields of activity. Such as in ESN, in industrial companies, in research laboratories…

In this post, we discuss AI in the workplace with our Chief Digital Officer, Felix Lemaignent.

Salary

AI expert salary

The average daily rate of an Artificial Intelligence Expert is between 700 and 1500€.

Training and education

AI expert education

To become an Artificial Intelligence Expert, you need to have a 5-year degree. You can enter this profession by having studied mathematics or computer science. However, you will need to continue your education and obtain a master’s degree or an engineering diploma. A specialized master’s degree or even a doctorate.

Also read 5 Online Courses to Get You Up-To-Speed with AI

After years of research and a lot of work, an AI expert can easily move on to new projects and join innovative start-ups in R&D, large companies, or research centers.

You can also read : 20 AI Experts You Should Follow

Find an Artificial Intelligence Expert job with Mindquest
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IT Infrastructure Job Descriptions Project Manager

Technical expert: Job description

Technical Expert

Use our template to create a compelling and comprehensive Technical expert job description to attract top talent.

The technical expert is generally a specialist who not only assists and controls but also informs and advises. He or she can particularly be involved in a project as a whole or in part. Here is everything you need to know about the technical expert job, the skills, education and training, career and salary expectations.

Are you looking for IT mission opportunities in the Tech and IT sectors on a freelance or permanent basis? Mindquest can help you find your next IT mission opportunity. Find technical expert missions by browsing our freelance and permanent vacancies available on our digital recruitment platform.

Technical expert: the job

Definition of the technical architecture

Always in accordance with the client’s strategy, the technical experts must analyze the company’s needs to implement the best possible solution to improve the business process. To do so, they will have to carry out internal audits to analyze the existing tools and possibly replace them with more efficient solutions.

They will then have to adapt the products in place to perfectly match the company’s structure. This phase will enable the solutions put in place to be tested to adapt them as much as possible to the company’s needs.

Training of the team

This phase is essential as it consists of training future users about the new product. The expert will assist in the deployment of the new products in order to provide maximum support to the new users.

Monitor and test the implemented tools

The technical expert must set up permanent tests to check the correct functioning of the elements that he/she has installed. In the event of a malfunction, it is important to be able to intervene quickly by analyzing and understanding the cause of the breakdown. As a problem can happen quickly, it is crucial to implement solutions to solve the problem.

Solving complex situations

The expert will have to explore all kinds of dysfunctions and propose a procedure to solve these complex problems. Of course, this procedure will have to be deployed in the company so that everyone can access it.

Also read our article about Project Management, roles, skills and career paths

Required skills of the Technical expert

Technical expert skills

Technical skills

The technical expert must have an excellent command of the technical solutions that fall within his or her field of competence. But it is also valuable to have a more general knowledge of properly technical solutions, such as a good understanding of one’s client’s field of activity.

Knowledge of English

Good knowledge of English is also important for understanding software documentation. In fact, much software is translated into English. The technical expert can attend training sessions in English on certain tools.

Listening, curiosity, rigor

The expert must be able to listen to the customers to respond as much as possible to their needs. Then, curiosity is essential to constantly seek new technical developments. Moreover, rigor seems indispensable. Indeed, to remain competitive, they must thoroughly assess the company’s needs to respond to them as best they can.

Self-education and versatility

The technical expert is a constantly evolving profession. In fact, always on the lookout for new technologies, the technical expert is in constant training to remain competitive. Versatility is also predominant in this profession. The expert must solve technical problems and train future users of the tools in-house.

Be a good teacher

Finally, he or she must be a good teacher in order to train future users of the tools that he or she will have put in place within the company. This training is provided both internally and externally.

You might also find our article on IT infrastructure: components, professional profile, and best practices interesting.

Context

Technical expert, context

Internally, the technical expert is in contact with the technical consultants, the support manager, the designers, and developers, and the product managers. Externally, he/she works with service providers, the client, the IT department, and suppliers. They are also in constant contact with future users.

Careers and Salary

Technical expert salary

Before working as a technical expert, it is preferable to have at least three years of experience in professions such as design and development engineer or IT project manager.
It will be possible for the technical expert to progress to the professions of business engineer, project manager, or technical director.

The average daily rate will be between €550 and €700.

Training and education

Technical expert education

It is possible to become a technical expert after obtaining a Bac+2 (DUT or IUT) but also with a Bac+5 (Engineering school, Master). It is then possible to train in a more specialized field. Finally, a doctorate may also lead to technical expert job.

Find technical expert assignments on our freelance and permanent IT recruitment platform, or join Mindquest so you don’t miss out on any opportunity!

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ERP & SAP Job Descriptions

How to implement an efficient ERP in 6 steps

implement an efficient ERP
implement an efficient ERP

Certainly, to implement an efficient ERP is a crucial task; choosing a cloud-based solution can make the process faster. However, since an ERP covers the entire range of business functions, it is important to perform all the necessary steps carefully and methodically.

Switching to a new system, or activating it from scratch, requires a major preliminary analysis, a careful migration and testing process, scrupulous staff training, and fine-tuning of the system.

For this reason, we at Mindquest have summarized the various phases of this process in the following 6 steps.

Flowchart of ERP implementation steps

Flowchart of ERP implementation steps

Also read the advantages and disadvantages of SAP

1. Discovery and planning

Firstly, discovery and planning is perhaps the most important phase: if done methodically, it helps reduce time, cost, and risk. This phase consists of researching and selecting a system, establishing a project team, and defining detailed system requirements.

2. Design

Then, by analyzing the hardware and software infrastructure in place, new and more efficient workflows and other business processes can be designed to take advantage of the system.

In particular, if the choice falls to a cloud-based ERP, it is critical to check the quality, stability, and security of Internet access. Systematic analysis of information flows is critical here. Single systems may, in fact, perform less well than industry-specific products.

At this stage, it is also critical to define a team responsible for the process. Since the implementation is a complex task, dedicating resources makes it easier to interface with the support team.

3. Development

In addition of having performed the audit and mapped the information flows, assigned functions and responsibilities, and identified the most suitable solution, the actual implementation phase begins.

This step consists of the configuration of access and permissions. The ERP is used by several users and in different capacities. It is therefore important to set permissions and roles for access according to one’s user profile.

It also includes the preparation of the data and processes to be migrated. Preliminary analysis helps to resolve any format incompatibilities in time. Centralized data management eliminates redundancies and duplicates

4. Testing

During this phase, it is valuable to continuously test the functions of the system and refine the development to solve any emerging problems.

Fine-tuning, it is to say, testing the system to gradually verify the results of the migration process and adjust any discrepancies in use and access.

5. Deployment

Once this phase is also completed, we move on to the actual operational verification of the new ERP. This is accompanied by staff usability testing.

With the new ERP fully operational, it is possible to observe its actual operation. Preliminary analysis and partial testing are useful, but the go-live is the real litmus test.

6. Support

In the initial break-in period, the work of the support and service team is critical. This is also the reason for choosing not only the ERP, but also the company that provides it.

Maintaining the ERP implementation after deployment helps keep users satisfied and ensures that the company achieves the desired benefits.

Last but not leas, the project team may remain responsible for the ERP system during this phase, but will focus on listening to user feedback and adjusting the system accordingly.

Further development and configuration may be needed as new features are added to the system. It is also critical to train new staff on the system to implement an efficient ERP.

Are you looking for freelance or permanent assignments in the ERP field? You can now apply for our Tech & IT job opportunities on our freelance and permanent recruitment platform.

You can also explore the role of the SAP FICO Consultant

Need advice on how to start or develop your freelance consulting business in tech or IT? Need to start a new permanent or freelance assignment? Join Mindquest and get support from our team of experts.

Categories
Data & Business Intelligence Job Descriptions

8 mistakes to avoid in Business Intelligence (BI)

8 mistakes to avoid in business intelligence (BI)
8 mistakes to avoid in business intelligence (BI)

IDC estimates that the business intelligence market will continue to grow at a rate of 8 percent through 2022. But despite the success of these types of business software solutions, most projects fail at some point in their implementation. What are the causes? How can they be avoided? To help you, we at Mindquest collected a list of 8 mistakes to avoid when it comes to Business Intelligence.

Need advice on how to start or develop your freelance consulting business in tech or IT? Need to start a new permanent or freelance assignment? Join Mindquest and get support from our team of experts.

Business Intelligence: decision-making technology

The purpose of Business Intelligence (BI) solutions is to provide information that facilitates decision-making with real-time data. Therefore, in an ever-changing environment, BI software is increasingly indispensable.

Moreover, the union between BI and Data Science is expanding the horizon of possibilities of Business Intelligence to limits that were unimaginable just a few years ago.

But in order for your company to benefit from all this business decision-making technology, it is necessary to carry out a good implementation.

The following are the 8 most common mistakes to avoid when it comes to Business Intelligence.

Also read our Business Intelligence Analyst job description

The 8 mistakes to avoid in Business Intelligence

mistakes to avoid Business Intelligence

Business Intelligence mistakes that companies often make are often the same. Therefore, let’s take a look at the “manual of bad practices” in Business Intelligence implementation.

Firstly, avoiding a BI software implementation problem means anticipating it, which is why it is necessary to know in advance.

1. Not defining the objectives of the software properly in the planning phase

To start, it is a big mistake to think that just by setting up a BI solution it will work by itself, as if by magic. Business Intelligence is just a tool, and it will work as long as it is handled with skill.

For it to work, the objectives to be achieved with the implementation need to be set from the outset. These must also be aligned with the business objectives. This is the only way to get a return on the investment in Business Intelligence.

2. Give all the power over the BI tool to the IT department

Related to the previous point, for the software to be aligned with business objectives, the implementation must transcend the IT department.

In other words, the more business-oriented managers and executives must actively participate in defining the objectives that the BI must meet.

3. Choosing a Business Intelligence technology that does not meet the requirements of the business

There is a multitude of software vendors with different technical and functional solutions on the market, and then there are customized solutions. Whatever your company may select, the software must be tailored to your business needs.

Be suspicious of one-size-fits-all solutions. Since the best business intelligence technology will depend, in most cases, on the size of your company, the sector in which you operate, the type of activity, etc.

4. Not doing a good job of integration

For the BI solution to deliver the desired results, integration with the company’s databases is crucial.

Companies that still rely on Excel for everything have a problem in this regard, and need a complete overhaul of their systems. BI that is well integrated with data from ERP, CRM, etc., is crucial.

5. Neglecting data quality

One of the consequences of not doing a good job of integrating with the company’s databases is poor data. But there are other reasons why data may be of poor quality, irrelevant or incomplete.

There must be controls in place to avoid loading erroneous data into Business Intelligence, ETL (Extract, Transform, Loud) processes, etc.

6. Prioritize the front-end and leave the back-end in the background

Although the purpose of a BI tool should be to present dashboards, reports, and charts visually that facilitate the analysis of information (front-end), the configuration of internal processes (back-end), which are responsible for processing all the information that is then to be displayed, should not be overlooked.

Giving equal importance to the back-end and front-end is crucial for choosing the right technology when implementing or developing a Business Intelligence solution.

7. Not sufficiently protecting your BI data

Certainly, developing a solution with self-service options that democratize data and extend it to more internal users is often beneficial to a company.

Mobility also enables more practical use of technology, allowing, for example, access to reports from a smartphone or other device from anywhere.

But all this can also pose a serious security problem when an employee views information to which he or she should not have access or an employee loses his or her smartphone, opening the company’s doors to any stranger. Effective controls need to be put in place to ensure legal compliance and company security.

8. Forgetting the end user

Last but not least, training the employees and professional profiles that must handle the Business Intelligence solution is fundamental if we want them to use it.

Low adoption is one of the main reasons why the implementation of BI in the company can fail.

A good training program is very useful, but it is not enough. The employee must understand why it makes sense for the company to use Business Intelligence, and why it is important for them to use it.

Also read the differences between Big Data and Business Intelligence

Conclusion

To conclude, Business Intelligence is the ability to visualize data in an easily interpretable way with powerful top-down navigation that makes it easy to get to the source of the detected problem.

If we associate it directly with information technology, we can say that BI is the set of applications, technologies, and methodologies that can collect and transform data into valuable and structured information that can be used and analyzed directly.

For this reason, it is important to know the most common mistakes to avoid in Business Intelligence, to convert information into valuable data for decision-making.

You can also read : 11 Best Business Intelligence Tools of 2023

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