Case Study Details

 

Offered Cloud-enabled data convergence to the USA’s leading consumer goods manufacturing company for better business outcomes

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Client Background

Client Background

The company is a major American manufacturer of household products that is headquartered in Ewing, New Jersey. While it manufactures many products, it is best known for its Arm & Hammer line which includes baking soda and a variety of products made with it, including laundry detergent.

Objective

The main purpose of the project was to create an on-premises solution for the client’s sales reporting structure as well as the flexibility to move their entire data to the cloud for faster processing time. The client wanted to generate rich iterative as well as precisely formatted reports, visually explore huge data and quickly discover patterns to make quicker decisions.

  • Country
    USA

  • Industry
    Retail / FMCG

  • Solution
    Cloud, Microsoft Azure, Machine Learning,
    Artificial Intelligence, Design Solutions,
    Data Engineering & Analytics, Digital Transformation

Challanges

Challenges

  • Lack of a customized platform and high need to modernizing infrastructure
  • A multitude of information was streaming in every day from various regions making it difficult for the client to maintain a central repository in their traditional IT infrastructure system
  • Sorting data through various tools like SQL and SAP, data sets, and spreadsheets was slowing down the growth and the success of the organization
  • The generation of the gross sales report in these traditional systems was not possible as the data was unstructured
  • Difficulty in describing the technical design of iGDW and addressing the detailed business drivers, context, and requirements for the gross sales
  • Absence of a reliable Gross sales reporting for the total international division with a breakdown of export and domestic channel
  • The Deliverable of this project is to implement the gross sales reports with
    1. Volume
    2. Customers
    3. Date
    4. Currency
    5. Brand
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Solution

The client wanted an on-premises solution for their sales reporting structure as well as the flexibility to move their entire data to the cloud for faster processing time. A modern enterprise needs a modern set of analytics – supporting big data and everything else and gain business insights and enhance business initiatives.

  • We provided our Power BI solution which is a cloud-based analytics service that gives a single and more comprehensive view of most of the business-critical data
  • Our Azure SQL Server Database service is scaled up during the data processing to reduce processing time and then scaled down once complete to minimize costs
  • In our solution, we integrated various data analytics features such as ETL (Extraction, Transformation &Loading), Data cleansing, Filtering, Deduplication
  • The platform will help the client in region-wise Data Searching & Data convergence
  • Our solution can easily perform Unstructured, Structure Data Handling & Data Modelling
  • The platform is also capable of Driving futuristic insights & visualization with the help of Analytics
  • In order to make the platform more robust and tech-savvy, we added modern technologies like NLP (Natural language programming), Machine Learning, Artificial Intelligence, etc.
  • The professionals at KCS created a cloud-based predictive analytics platform that identifies and predicts trends in real-time from big data streams, including social media analytics with help of Node Js, React, Mean.Js, firebase, and elastic search
  • We leveraged a stellar platform with the use of full-stack technologies such as Node, Angular, React, React Native, ELK that allow customers to import, transform, and filter their data from the Hadoop data lake and create visuals on it. With the help of that tools, customers can perform analysis on their data with various pre-created visuals, AI & ML algorithms

Case Study Solution

Project Highlights

Dashboard: Brand performance

Dashboard: Brand performance

Dashboard: Customer performance

Dashboard: Customer performance

Yearly / Monthly / Quarterly Reports

Yearly / Monthly / Quarterly Reports

Regional Sales Reports

Regional Sales Reports

Brand Performance Report

Brand Performance Report

Sales by brands and customer

Sales by brands and customer

Machine learning Algorithm

Machine learning Algorithm

Vertical & Horizontal Bar Charts

Vertical & Horizontal Bar Charts

J Query Gauge plugins

J Query Gauge plugins

Visual Representation of Gross Sales by Country through Maps

Visual Representation of Gross Sales by Country through Maps

KCS Approach

KCS Approach

Our astounding solution helped the client dynamically adjust tactics and updates in real-time while converting the bottom line into top strategies. It enabled them to leverage live data and real-time dashboards to review current sales performance. The client could easily identify underperforming areas.

Outcome

Outcome

  • Our intelligent Power BI solution and IT Modernization helped the client centralize its huge amount of data, connect to hundreds of data sources, simplify the data preparation, generate sales reports faster and easier as well as drive ad hoc analysis
  • It helped the client interact with the sales team across various regions through shared interactive visuals while quickly tracking sales trends to optimize business strategies
  • Moreover, determining the variance between actual revenue and sales targets by segment was simplified
  • Also, the platform was user-friendly enabling the client to reach new heights as per their changing demands
  • They could quickly generate BI gross sales reports based on consumer behaviors, product sales, and brand popularity
  • We provided a simple yet intuitive and collaborative way to the client in order to solve their everyday business problems
  • To help the client make most of their sales data we implemented an Azure-based cloud solution to abstract, store, visualize and analyze core business data
  • With the Power BI model and reports, the client was able to generate time intelligent reports based on month-to-date, quarter-to-date, and year-to-date, across the available actual and target data
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Tech Stack

Spark
Elastic Search
Kafka
Scala
Mean Stack
Power BI
Node Js
Angular Js
MongoDB
Mean.js

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