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

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.

Business Challenge

Build a secure and scalable data aggregation and analytics cognitive platform that transforms key business processes.

Solution

IBA Group developers worked on the Cognitive Enterprise Data Platform (CEDP). This platform makes it easy to get, share, and integrate enterprise data. Various business units of the company interact with the platform as producers and consumers of data.

Result

CEDP currently contains over 100 enterprise data assets. Datasets include customer master data, product offering master data, unified taxonomy, and more.

CEDP has big data analytics capabilities such as BigSQL, HDFS, DashDB for performance-based analytics, unstructured data annotation capabilities, machine learning, deep learning, and access to IBM Cloud Services.

Business challenge

Improve the quality of customer analytics and services. Collect additional information from public sources: social media and forums.

Solution

The solution collects data from various external sources. Using semantic and cluster models, it identifies objects of interest. It complements existing dictionaries with business terms, calculates a satisfaction rating based on sentiments in comments and reviews, and visualizes sentiment data. Visualization is based on Qlik Sense, however any BI system can be used.

Result

The solution is applicable to any enterprises and organizations that provide services or sell products to a wide segment of the population, which can be discussed on forums, edicated websites and social media.

Business challenge

The company set an objective to assess the efficiency of budget spending on the advertising of manufactured drugs, and to build an optimal advertising strategy.

Solution

IBA Group experts together with methodologists from the consulting company analyzed the costs of advertising in the media, on TV and radio, outdoor advertising and online promotional campaigns. Five-year data were used to take into account the impact of economic factors and seasonal fluctuation. Specialists created an interpretive forecast model with a seasonal component and identified key parameters that influence brand loyalty.

The results of the study showed that outdoor advertising is greatly overestimated and its efficiency needs to be evaluated more carefully. In addition, advertising a single product in a product line may increase sales of all products in a line – the so-called “halo effect,” when brand visibility due to the main product is extended to cover the entire line.

Result

Marketers obtained new tools: a dashboard for comparative analysis of the sales level and advertising efficiency in various channels, and a calculator for the optimal allocation of budgets for the forecast period. They were used to identify budget limits, above which there’s no point to invest in promotion, because the efficiency of advertising campaigns decreases sharply and does not lead to expected sales.

Financiers and budget owners use accurate data to plan investments in each advertising channel for various estimated levels of advertising budgets.

Challenge

The customer aimed to test feasibility of a cognitive automation technology for its business processes. The pilot business process consisted in validation of the tax amount charged in a vendor contract. Tax rates vary for different groups of vendors and are defined in the customer’s database.

Process Requirements

1. Achieve overall business process accuracy of 98 percent
2. Reduce manual time spent on one process by 50 percent
3. Train and support customer’s team to build automation for an SAP case.