Challenges

1. Merging data from diverse HR platforms
2. Navigating multiple disparate HR systems, which had created data redundancies and inconsistencies, making it hard to extract a single source of truth
3. Development of data flow mappings
4. Data quality management implementation
5. Data masking for personally identifiable data based on access level
6. ETL design and implementation data integration into the global DWH solution
7. Making sure that the cloud-based HR solution was compatible with other business tools and systems used in different departments, which was crucial for holistic business operations

Goal

Build SaaS for offices all over the world to manage the administrative processes required to track and support employees

Results

1. HR teams, managers, and employees have secure access to necessary data from anywhere and real-time analytics
2. Migration for 39 countries implemented successfully, taking into account all regulations
3. Developed, reinvented, and modernized the HR system for all HR-related tasks and procedures
4. Advanced encryption and security protocols ensured sensitive HR data is protected
5. Collaboration and self-service capabilities make employees more engaged in teamwork. Satisfaction has increased by 50%
6. Various HR tools and applications were easily integrated, breaking data silos

Challenges

1. Implementing data processing techniques and methodologies to calculate pivotal KPIs
2. Interactive Dashboard redesign on the QlikSense platform, to provide intuitive insights for stakeholders
3. Ensuring that the data solutions not only met the operational needs but also adhered to stringent pharmaceutical regulations
4. ETL design and implementation data integration into the global DWH solution
5. Implement streamlined data processes

Goals

1. Create a centralized data solution with Data Lake for CRM and merchandising data
2. Redesign sales activity, product visibility and distribution dashboards for finance analytics and managers for future optimal purchases

Results

1. By centralizing and streamlining data, the pharmaceutical company derives x2 quicker insights from clinical trials
2. Improved product visibility and placement
3. Consolidated data system facilitates easier and more accurate reporting, ensuring compliance with global regulatory standards
4. Automated and enhanced control of merchandising activities by identification of planogram compliance issues
5. No more time wasted searching for data across multiple systems. Our teams could now focus on analyzing the data and deriving actionable insights
6. The client benefits from significant cost savings in terms of both infrastructure and manpower

Challenges

1. Implementing data processing techniques and methodologies to calculate pivotal KPIs
2. Raw Data Warehouse (RDWH) used traditional on-premises infrastructure for its extensive data needs. It had a three-tier overloaded database system
3. A performance issue involved with creating an environment for application testing, as data cannot be easily or quickly copied from production to test
4. Costly hardware and software licensing
5. Interactive Dashboard redesign on QlikSense platform to provide intuitive insights for stakeholders

Goal

Create a platform to encourage self-service analytics and efficient data-driven decision processes

Results

1. Costs have been reduced by 30% annually
2. An improved user experience that refined data querying and exploration through a web Ul
3. Enabled data scientists and other programmers to leverage Snowflake’s scalable processing power to run AI/ML algorithms efficiently
4. Using Snowflake in the Cloud enables faster and easier recovery in case of a technology-related outage
5. Empowered users with self-service analytics, enabling them to explore and analyze data independently, uncover insights, and make data-driven decisions
6. System scales based on demand. This means reporting is no longer affected or delayed due to spikes in system demand

Challenges

1. Data analysis and visualization from different sources through all departments
2. Hypothesis validation, implementation and the deployment of predictive models
3. Setting up Big Data infrastructure in AWS Cloud
4. Implementation of data quality management
5. Row Level Security implementation for secure access
6. Costly hardware and software licensing

Goal

Create a road traffic analysis solution to manage big volumes of data and cut financial losses

Results

1. The company benefits from up-to-the-minute insights into traffic patterns and congestion, enabling it to provide more accurate and timely information to its customers
2. The Client’s management now makes better-informed decisions, leading to optimized operations, and improved service quality
3. The risks of financial losses are eliminated with the help of protection against unauthorized access
4. Data leaks and compliance violations were eliminated

Challenges

1. Seamlessly blending modern solutions with the financial institution’s existing legacy systems
2. Providing systems that can handle exponential data growth without performance hitches
3. Navigating changes in financial regulations across regions
4. Continuously innovating in a rapidly evolving technology landscape
5. Data Ocean Design based on the Data Vault methodology
6. Presentation Layer Design for reporting systems – Mart and Dimensions
7. Row Level Security implementation for secure access by end users to the reporting system

Goals

1. Develop a Cloud-Based Financial Risk Analysis Platform
2. Build Purchase to Pay Golden Model
3. Design a User-Friendly Order-to-Cash Reporting System

Results

1. Optimized efficient data management, operational processes: transaction processing, risk assessment customer service
2. Enabled data scientists and other programmers to leverage innovations such as AI and ML efficiently
3. Created a data model for deep analysis, strategic planning, and forecasting
4. Built Purchase to Pay and Order to Cash Golden Models that allow end users to construct reports themselves in a BI tool

Background

One of the business units of the customer’s company was previously a stand-alone company, so they used non-standard software to create reports. Employees of this business unit had to use MS Excel to bring their reports to a standard form.

Business Challenge

Automate the generation of standard reports adopted in all business units of the company.

Solution

To automate report generation, we developed SSDM (Security Systems Data Mart) — an integrated data warehouse. This warehouse contains data from their custom systems previously used by this business unit, as well as standard data from the systems of other business units of the company. This data contains information on payments, services and accounting. Automatic reports are generated in Cognos.

The developed system has a complex business logic that is constantly changing and evolving. In the course of the project, there was a migration from one contract management system to another, which has a different data model. Then the system was migrated to interact with clients to another service. These changes were considered in the operation of the data warehouse and the integration was completed successfully.

Result

Most of operations that employees used to do in MS Excel are now performed automatically in SSDM. We configured automatic reporting in Cognos. Also, the developed data warehouse is used by other business units of the company as a data source for reports.

Previously, it took most of the month to generate reports, but with the introduction of the new solution, this time has been reduced to 2-3 days.

Background

The customer is the company’s business unit engaged in training management. Previously, reports on the implementation of training programs were prepared manually: they collected data from various training systems and summarized them.

Business Challenge

The company has several training apps that collect a variety of data about students, instructors, and training programs. This data needs to be collected in one system and automate the reporting process.

Solution

Since it was required to build a solution framework in a short time, we decided to use an open source solution. The IBA Group team developed a test version of the data warehouse with integrated Tableau BI system. Dashboards and reports are now created in this software.

The challenge of the project was that the various applications of the training platforms had to be taught to communicate with each other. For example, there is an application where employees take courses and another application where they provide feedback on these courses. The task was to write a utility that would automatically forward users after completing the courses to the feedback page which already contained the details of the course.

Result

Previously, report preparation using MS Excel took about a week. Now this process is fully automated with a ready-made dashboard in Tableau.

The customer is also able to track and analyze the content: demand for courses, percentage of fully-completed courses, and number of certificates received by students.

Background

А huge global company with a strong technology focus turned to IBA Group with the task of transferring their client’s infrastructure to cloud services. At the time of the beginning of cooperation, the end customer of our client used a lot of data storage for the following internal service tasks:

• production cost tracking;
• dialer’s information;
• providing information to dealers,
• information about clients, employees.

The main part of the infrastructure was based on the Oracle database and the Informatica Power Center ETL tool, as well as many other tools such as Cron, Shell Script, Java, JS.

Several years ago, the company’s management decided to migrate the entire infrastructure to the cloud. During modernization, the company brought production processes to a single standard, increasing its structure, including a unified approach to development, implementing an approved technology stack, and ensuring quality control of development.

Business Challenges

During the modernization process, the end client encountered the following difficulties:

1. The existing services of the company were slow, which impacted all processes — from data analysis to hiring employees.
2. Frequent failures due to errors within the services led to a partial loss of data and the inability to make management decisions, prepare accounting reports, prepare data on the movement of warehouse resources, and more.
3. Permanent delays in providing new services due to the slowdown in development or the impossibility of their implementation, led to a decrease in the company’s attractiveness among customers.
4. Scaling within the framework of the old infrastructure could not be carried out without extra payments, due to the low flexibility of vendor licensing offers.
5. Recruitment of the necessary employees such as full-stack developers presented difficulties due to the huge variety of technologies used; cheaper resources were not of the right quality or up to the high standards of the company.

Key Objective #1

Migrate company services to new infrastructure in the cloud.

Key Objective #2

Tailor AWS vendor migration offerings to company services.

Solution Highlights

The customer formed a separate team that was responsible for the innovation and unification of disparate systems into a single infrastructure. IBA Group provided engineers and architects to form custom teams to participate in the adaptation of infrastructure modernization solutions, developing the top-level structure of the entire ecosystem, as well as general approaches and rules for each system separately.

After giving recommendations for the development and auditing of the process, the IBA Group team directly implemented this migration. To improve the quality of decisions made at the architecture design stage, an AWS vendor was involved.

Due to the business’s specific features, each area had its own architecture, for which separate teams were created that were responsible for its adaption and improvement. They were also involved in the transfer of existing services for their area to cloud technologies — AWS Glue, PySpark, ECS, Kubernetes, EMR + PySpark.

One of the important conditions was a “seamless” transition — teams during the migration process ensured that access to existing services remained uninterrupted.

Project Results

Benefits the client received by moving data management to a cloud service:

1. Increased fault tolerance by fixing bugs and using ready-made cloud-platform services for interaction between different customer services.
2. Continuity of current services during the migration process was maintained.
3. Cost reduction in the form of refusal of some server capacities due to the transition to the cloud service.
4. Flexible planning of financial expenses for scaling due to the pay-as-you-go system provided by the cloud solution.
5. Reduced time for recruiting specialists in the IT department by unifying the requirements for them, defining clear rules, and specifying the technology stack.
6. Reduction of the number of narrowly focused specialists without full-time employment due to their retraining in the technology stack adopted by the company.

Background

Previously, the bank did not use systems to automate the accounting of procurement processes. The documents were prepared in hard copies which were considered/approved at the meetings of the working groups. All documents were stored in folders, employees also made their electronic copies.

Main problems that the bank wanted to address:

• lack of a central repository of all documents related to procurement processes;
• lack of transparency in procurement processes;
• long lead times for the procurement of goods and services;
• lack of reporting on procurement processes and their efficiency;
• lack of budget expenditure reports.

Business Challenge

The Bank submitted a request to automate the accounting of procurement and contracting in the context of its business activities. The new system was supposed to be the last in the trio of applications that were developed at different times. First two applications:

• EDW: Enterprise Data Warehouse and reporting system based on IBM Cognos;
• ABFPS: Automated Budgeting and Financial Planning System.

It was necessary to create a unified accounting system for all documents related to the procurement of goods and services, with their subsequent approval and supervision over the execution of expenses budget. Upon conclusion of the contract, keep records of primary accounting documents and monitor payments. The system was to be built on the basis of the bank’s existing infrastructure based on IBM products (DB2, FileNet, WebSphere, Integration Bus) and integrated with the personnel records system, budgeting system, Enterprise Storage, and the bank’s operating system.

Solution

The IBA Group team has developed a bank business management system based on the terms of reference elaborated jointly with the customer. The system has a client side for working from a browser and a server side for business logic. The approval of documents was organized through a dedicated business process management system. An enterprise service bus was used to integrate with related systems of the bank. All documents created within the system are stored in the document storage powered by FileNet.

Result

A unified system of accounting for all documents in the process of purchasing goods and services has been created. Now all documents are approved in a single system with the ability to access information about the document itself and its approval route. During document approval, the available free budgets for procurement are monitored. Business is able to generate a variety of reports on the procurement processes and execution of expenses budgets. A unified catalog of purchased goods and services has also been created. For all contracts, documents on contractual performance and payments made are available together the capability of automatic payments.

The system has been in commercial operation since January 2019. During this period, about 95,000 documents were created. Now the project is in the support and development stage.