Transforming Analytics and Reporting through Data Warehouse Implementation

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About the Client
NDA, a stalwart in the market for nearly 30 years, follows an omnichannel model, conducting sales through its dedicated online platform and maintaining a robust network of 260 franchise stores nationwide. This positions it as one of the leading automotive chains in Kyrgyzstan, specializing in vehicles for various age groups and garnering customer appreciation evidenced by winning the Service Quality Star 13 times.
The company approached us with the objective of streamlining its data analysis process. The existing approach involved the company's team of analysts utilizing various tools and data sources. However, the process was cumbersome, requiring analysts to request necessary data from IT every time they wanted to create a report on a specific automotive topic. This procedural bottleneck hindered the swift and flexible analysis of crucial information in the dynamic car industry.
Problem Statement
  1. The company required a unified and consistent source of data for analysts and other experts within the organization within the automotive industry.
  2. The organization sought a methodology to rapidly analyze automotive data, test hypotheses, and generate reports in a creative and agile manner.
  3. The desired tool needed to be developed utilizing the current on-premises infrastructure and leveraging the Splunk tool previously implemented by the company in the automotive sector.
Our Approach
  1. Requirement Analysis and Planning:
    • Conduct thorough analysis of business requirements.
    • Define key metrics and KPIs for data analysis.
    • Develop detailed roadmap with project milestones.
  2. Data Modeling and Schema Design:
    • Utilize Star, Snowflake, and Fact Constellation Schemas.
    • Define data structures and relationships.
    • Ensure alignment with business needs.
  3. Data Warehouse Implementation:
    • Leverage Splunk for constructing the warehouse.
    • Aggregate data from ERP, e-commerce, and loyalty systems.
    • Design data ingestion pipelines.
  4. Analytics Enablement:
    • Empower analysts with self-service capabilities.
    • Provide training on accessing and querying data.
    • Foster data-driven decision-making culture.
  5. Analytics Enablement:
    • Monitor and optimize query performance.
    • Scale infrastructure resources as needed.
    • Establish maintenance procedures for the warehouse.
Our Solutions
  1. To address the company's reporting and data analysis needs, we initiated a thorough business requirements analysis. This process laid the foundation for our subsequent actions.
  2. Following the establishment of these business requirements, we developed a data model utilizing the Star, Snowflake, and Fact Constellation Schemas. These schemas, designed specifically for analytical databases, enable the rapid and efficient execution of intricate queries and data analyses.
  3. The selected data underwent a process of cleansing, transformation, and thematic grouping to streamline the work of analysts. Subsequently, we constructed a data warehouse leveraging the Splunk tool, a tool already in use at the company. Within this data warehouse, we aggregated data from various company systems, encompassing the ERP, e-commerce, and loyalty systems.
  4. To accommodate varying needs and priorities, different data types refresh at different intervals; for instance, online sales data refreshes more frequently and dynamically. This dynamic approach ensures that the entire system aligns seamlessly with the company's requirements, maintaining a high level of efficiency.
  5. The implementation of an automated data flow has significantly enhanced the agility and creativity with which analysts can work with available data. This empowerment allows analysts to easily delve into individual product sales analysis and explore relationships between sales in different channels and factors like seasonality and time of the year.
Our Outcomes
  1. Single Source of Truth: Presently, analytical data from crucial systems is uniform and accessible within a centralized repository.
  2. Improved Reporting Process: Analysts can efficiently produce the necessary reports without requiring IT intervention or consuming IT resources.
  3. Advanced Analytics: A team of analysts has the capability to conduct thorough analyses of individual product sales and customer behaviors.
  4. Automatic Data Flow: Data undergoes updates based on a predetermined schedule and frequency.

Get In Touch

Thank you for your interest in Ant Tech Company. We welcome inquiries and feedback. Please feel free to reach out to us using the contact details below:

Address

Address

Dallas, TX 75032, USA
Bishkek, Kyrgyzstan

Phone

Phone

+1 214 256 3310
+996 995 000 360

Email

info@ant-tech.io

LinkedIn

LinkedIn

@ant-techio

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