Data and Advanced Analytics

Accelerate your business value with data and analytics to gain valuable insights while delivering AI-powered solutions using data visualization and data governance

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Data and Advanced Analytics

Data-Driven Enterprises

In this digital era, enterprises are undergoing a transformation that requires empowering the business with data and insights to remain competitive. Being an analytics-driven enterprise will allow you to gain valuable insights into your business and give you a significant advantage in the marketplace. 94% of enterprises say data is essential to business growth. Data and analytics are the strategic assets for managing your business risks, increasing productivity, gaining competitive advantage, growing revenue and improving customer experiences.

According to Gartner, nearly 97% of data remains unused within the organization. Thus, leaving a gold mine of insights and patterns that organizations can leverage for better customer experiences, competitive advantages and even new revenue channels. Data-driven enterprises are leveraging analytics and intelligence as the foundation for innovation, better decision making and improved operational efficiency.

Hyper Personalized Experiences

Deliver personalized and curated experiences for your customers, partners and employees with analytical solutions

Business Model Innovation

Drive new revenue channels and innovate your future business models by harnessing your data and the derived insights

Prescriptive Decision Making

Empower your organization to be more proactive through a data-driven prescription that enables informed decision making

Business Process Optimization

Gain competitive advantages through real-time visibility into business operations that in turn optimize critical processes

Our Capabilities

We are your partner of choice as you embark on a data-powered transformation journey where the next wave of bespoke, data-driven analytics catalyzes revolutionary outcomes and establishes new benchmarks. At Miraclesoft, we harness the synergy of AI and deep human insight to empower your enterprise with unparalleled data sovereignty and fueling fact-based decision-making.

Miracle’s Data and Advanced Analytics CoE are experts at unveiling fact-driven strategies that catapult businesses to the forefront of their industries - including deep knowledge of domains such as Manufacturing, Logistics, Healthcare, Retail, Financial Services and beyond.

Data Management and Governance

Establish a secure and trusted data foundation that empowers analytics initiatives through meticulous stewardship and data integrity

Data Engineering and Analytics

Empower your businesses data and eliminate data silos by transforming disparate raw data into refined assets that enable data-driven solutions

Advanced Analytics and AI/ML

Elevate your data into a strategic asset by infusing AI-powered analytics and enabling prescriptive and predictive decision making for your business

DataOps and Managed Services

Streamline the continuous delivery and availability of your data through an agile data lifecycle that covers data capture to insight generation

Our Services Offerings

With over 3 decades of industry expertise, Miraclesoft is your partner of choice for data-driven initiatives that power your digital transformation journey. Our Hybrid Delivery Model combined with a passion for innovation has helped numerous Fortune 500 enterprises create future-proof data strategies, establish secure and scalable analytics environments and rapidly innovate with AI-infused solutions.

Envision a team of data strategists, assembled to empower your business with the power of data, advanced analytics and AI/ML. We deliver business-transforming outcomes through innovative technology solutions.

Data Strategy and Architecture

Develop flexible and scalable data architectures that address future volume growth, modern security needs and speed to market

Outcome Based Delivery Sprints

Engage our CoE team to deliver predefined outcomes including data pipelines, visualizations and data platforms

Agile Analytics Product Squads

Assemble agile product squads in a cost-effective framework that help deliver analytical products and assets for your business

Software Licensing and Subscriptions

Streamline your licensing and subscription management including premium discounts with our Software Sales team

Rapid Innovation Prototyping for AI/ML

Accelerate ideation and thought leadership by engaging our Innovation Labs for your AI/ML prototyping exercises

Analytics Platform Modernization

Transform your business model with self-service analytics, cloud data platforms and AI infused data products

Strategic Talent Augmentation

Empower your business to achieve more by acquiring industry-best talent through our AI-driven talent acquisition workflow

Managed Services and Support

Experience SLA-driven, cost-optimized managed services and infrastructure assurance through our DataOps Command Center

Let us strategize your data journey, where informed decisions aren't just made - they’re engineered

Miraclesoft’s core mission is to transform complex data into decision action, rapidly innovate product development, transcend customer experiences and prescribe business strategies. Our expertise lies in architecting comprehensive data solutions that crystalize raw information into valuable insights, accelerating growth and pioneering market leadership.


Powering Advanced Analytics with Snowflake for a National Retailer

Application Development and Delivery
Cloud Application
Business Challenge

Our customer is a privately-owned department store chain, looking to migrate from their legacy, on-premises data warehouse based on Teradata to a modern, cloud-based data warehouse.

They were looking to achieve better data insights for their business while also improving their data platform’s scalability and resolving batch jobs performance issues. They wanted to provide a platform that could address their real-time decision-making needs for same-day sales and improve query performance for analytics.

As a part of their architecture, they chose to combine Azure’s Data Lake capabilities with Snowflake as their Data Warehouse. This migration was a part of the customers’ Enterprise Reporting and Analytics Modernization initiative. The main drivers of the migration included modernization, compute scalability, cost efficiency, and enablement for self-service analytics.

Our Solution

Team Miracle was instrumental in the data migration and warehouse operationalization with Azure and Snowflake,

  • Implemented a purpose-built retail Data-as-a-Service (DaaS) solution designed specifically to speed and simplify retailers’ journey to holistic
  • Migrated data integration flows (ETL/ELT) using Talend for the data acquisition from flat files, SQL Server, and Oracle
  • Migration and Data Validation for the Teradata Schema and Objects to Snowflake Schema and Objects
  • Converted data types and objects to Snowflake compatibility along with row count, aggregation, and string hashing-based data validation
  • Implemented their data lake for structure and unstructured data to the stage before the Data Warehouse
  • SnowPipe-based ETL integration with Azure Data Lake Storage to transform and load data into Snowflake
  • Implemented real-time data load using Attunity Replicate for CDC loads from source systems to Snowflake in near real-time
  • Migrated (Repointing) BI reports and Consumer applications including Alteryx, Tableau, MicroStrategy, and R along with structural validation and data validation for business-critical reports
Customer Benefits
  • Fully operationalized and migrated to modern data platform with Snowflake and Azure
  • Ability to independently scale compute and storage (business users, query users, and batch users) for high availability and real-time reports
  • Gain cost-efficiency through a pay-as-you-go model, cloud economics, and on-demand analytical compute
  • Enabled quicker time to market for innovative new use cases and self-service analytics through Snowflake and Azure Data Lake
  • Improved performance - large queries ran 90% faster for medium Warehouse, 96% faster for XL Warehouse
  • Better scalability with zero failures across 480+ queries by 50+ concurrent users on Snowflake, compared to 30+ concurrent users on Teradata with several failed queries
Technology Scope
  • MicroStrategy, Tableau, Azure, Azure Data Lake Storage, Snowflake, SnowPipe, Talend, Oracle, SQL Server, Azure Active Directory, Attunity Replicate

Modernizing Visualizations and Reports with Power BI for an Apparel Manufacturer

BigData and Analytics
Business Challenge

Our customer is a leading basic apparel brand that is setting new standards for design and sustainability. The business challenge that our customer was facing was around analytics and reporting. Also, the company was losing money as they did not have a good accounts receivables analytics system.

They had a large data set but they were not able to analyze as they would have liked, just because the data wasn't structured and wasn't ready for reporting purposes.

The business challenge we were out to solve with this project was creating a data warehouse of multiple data sources coming together and then creating best-in-class reports using Microsoft Power BI as the reporting solution.

Our Solution
  • Our solution for this project included creating a framework of data ingestion processes and creating data pipelines from multiple different sources of data going into Microsoft Azure Data Lake as well as creating a data warehouse reporting schema on an SQL server
  • The data ingestion framework included the data pipelines, the data connections as well as error handling structures so that any data-related issues could quickly be reported back to the business and a solution could be worked upon
  • Microsoft Power BI was used to connect to the SQL server to provide a reporting structure
  • The data in the SQL server was refreshed multiple times during the day, whereas in the Power BI reports, some of the reports were running on the batch data in the Power BI while some of the reports were running in the real-time mode
  • As part of the project, we created a complete end-to-end AR (Accounts Receivables) analytics platform which helped the customer to have a complete and true vision of their AR
  • The customer had plans to implement machine learning to understand and predict in a better way to understand the customer demand and taste shift. Currently, we are in the third phase of the project where we are working on finding those machine learning use cases and utilizing the Microsoft Azure platform to implement the advanced analytics complete solution for our customer
Customer Benefits
  • There were multiple benefits that this project provided to the customer, the first one included a very minimal maintenance cloud environment and a complete end-to-end fully automated data pipeline as well as a database, and data warehouse solution for their reporting needs
  • With this analytical solution, their business was able to take action on changing market conditions as well as customer demands faster and effortlessly
  • Were able to improve their turnaround time for processing customer applications and hence improve overall customer experience
  • Experienced reduced errors in the overall process due to automation
  • Allowed their Server administrators to spend their efforts on more value-added tasks rather than on manual maintenance
Technology Scope
  • Microsoft Azure Data Lake, Microsoft Azure Data Factory, Microsoft Synapse, Microsoft Azure SQL Server, Microsoft Power BI Reporting

Establishing an SAP-based Analytics Solution for a Furniture Manufacturer

Big Data and Analytics
Business Challenge

Our customer is one of the oldest and largest manufacturers, importers, and marketers of residential and contract upholstered and wooden furniture products. Below are a few challenges that were faced by the customer,

  • The current approach to creating financial reports was based on an Excel spreadsheet which aroused numerous challenges, including human, programming, capacity limitations, and many more
  • It required multiple data sources, including the legacy system to create consolidated reports which led to a huge processing time
  • To migrate the master and transactional data onto the new system, they were looking to upgrade their legacy platform from SAP S/4 Hana 1610 to 1809

They were looking for a modern and robust solution to build an enterprise data warehouse that could serve the existing and future needs for reports, dashboards, and analytics.

Our Implementation

  • Made an initial assessment and discovery session from which we designed and built a data warehouse system on Microsoft SQL Server that allows them to access the data coming from multiple data sources
  • Automated data acquisition and transformation using nightly batch jobs and workflows using Informatica Cloud Services
  • Designed enterprise data model and schema design which serves their ongoing analytical and reporting needs
  • Created a new migration strategy that includes extracting and transforms relevant products only and opening transactions to the new system
  • Implemented new number ranges as per the new system configurations
Customer Benefits
  • Centralized data repository for growing business requirements and business units
  • Data warehouse solution for analytical purposes using a fully automated environment to extract, transform, and load the data using scheduled jobs
Technology Scope
  • Informatica Intelligent Cloud Services, MS SQL Server, Tableau, SAP Legacy Transfer Migration Cockpit (LTMC)

Anomaly Detection and Trend Analysis in Logs for an Automotive Giant

Application Development and Delivery
Cloud Application
Business Challenge

Our customer is one of the largest Automobile manufacturers in Michigan. They were looking for a platform or a service to collect, store, and maintain sensitive real-time data and have the ability to build advanced machine-learning models on the data. As they were having the threat of Data breaches that could cost them a fortune.

It could only be restrained by analyzing the database logs to find and prevent any malicious activities in real-time, as early detection can save millions of dollars.

Our Implementation
  • Initially, we stored all the data received from multiple sources in their SQL Server databases
  • Built a solution to detect any anomalies or violations on their data by gathering SQL server
  • Built Machine Learning models to perform analytics on the database logs in real-time
  • Implemented search and analytics solution on the Lakehouse using Databrick and AWS
  • Lakehouse combined the usage of data lake and data warehouse into a single storage layer and uniformity was maintained throughout the organization on any changes in the data as the data is stored in a single location
Customer Benefits
  • Logs can be backtracked using time travel which helped them avoid any unwanted transformations in the data
  • Providing end-to-end streaming pipelines allowed them to not only collect data in real-time but also analyze and send alerts
  • Storing the data in a single location improved accessibility and easily performed analysis
  • Search and visualization service was paired up with the analytics service to help them build quick and effective models and understand unstructured logs better
Technology Scope
  • SQL Server, Machine Learning, AWS, Databrick, Lakehouse

Transforming Data for Better Governance and Management for an International Airport

Application Development and Delivery
Cloud Application
Business Challenge

Our client is one of the major international airports that provides services to more than 200 destinations. They were looking for a solution that addresses gaps in metadata management, data governance, and business knowledge management.

Our Solution

We provided a solution to support data stewardship and improve the quality of their data.

As a part of the implementation, our team:

  • Build a single source data library platform from various data sources and IOT/Sensors
  • Set up a full-fledged Data Lake environment for near real-time, real-time, and IOT/Sensors reports and analytics
  • Install and configure Informatica EDC, Informatica Axon, and IDQ in Production and Sandbox environments
  • Create customer’s Data Catalog, Classification/Definitions, and Governance operational playbook
  • Assist with executing data governance use cases and workflows for Informatica EDC and Axon integration patterns
  • Built a self-service analytical platform with strict monitoring by data governance, security, and compliance team
  • Deliver an E2E value use case, showcasing metadata reverse lineage from reporting to source, the integration of business terms with technical metadata and data quality rules from metadata resources
Customer Benefits
  • Single source of data inventory paved a way for users to use as one database repository for various reports and analytics/forecasting models
  • Enhanced customer safety measures and instant public safety security dispatch
  • High standards of data quality and data management
  • Better passenger forecasting, flight landings, and cargo onboardings
  • Seamless data integration with Informatica IDMC and MDM enabled faster systems integration, CRM, governance, and information management
  • Unifying the capabilities of data discovery, data lineage, data profiling, data quality, and business glossary creation enabled efficient self-service analytics and data governance
Technology Scope
  • Informatica PC, IICS (IDMC) and Mulesoft
  • Informatica Axon, Informatica EDC, IDQ, Oracle, Snowflake, Tableau
  • Powershell, Python and Shell
  • DataIku for Advanced Analytics/ML& Business Models
  • MS Azure, Snowflake, and Oracle

Unifying Data to Provide Valuable Insights for a Leading Global Coatings Provider

Big Data & Analytics
Cloud Applications
Business Challenge

Our customer is one of the leading manufacturers and distributors of high-performance coating systems. They are known for their high-quality products and brands, supported by market-leading technology and customer service.

They were looking for a solution that unifies data on their products and items with various attributes inclusions. In addition, they want to build governance over their master data to enhance business relationships and gain better insights and knowledge management.

Our Solution
  • Establish business rules across unified MDM, data integration, and data quality on a single platform
  • Built a solution Re-identify attributes to define MDM 2.0 logical data model for Material, Vendor, and Supplier based on existing fields and considering future data model expansion
  • Consolidate duplicate data into trustable data version and define a Golden Template strategy potentially be inherited across all domains
  • Build an integration architecture to achieve near real-time data flow and ensure data sync between system of records and system of origin before downstreaming applications data consumption
Customer Benefits
  • Seamless data integration with Informatica MDM resulted in better business relationships, insights, and knowledge management
  • Establishing unified rules with utmost accuracy resulted in the availability of up-to-date, trustable data across the organization
  • Redesigning key system integration pipelines reduced data silos with enhanced consistency
  • Building governance over master dataPre-built connectors enabled quick-decision making through SAP, Ariba, Salesforce, and CFIN integrations
  • Improved attribute management enabled efficient handling of materials, vendor and supplier data
Technology Scope
  • Oracle DB, Salesforce, SAP Ariba, SAP S4 HANA and Informatica MDM
  • Informatica Power Center and IICS
  • JAVA Programming
  • Power BI

Strategic Partnerships

Miracle is proud to be aligned with some of the top technology leaders in the realm of Data and Advanced Analytics. Our strategic alliances empower us to deliver cutting-edge, enterprise-grade solutions to our global customers and allow us to be at the forefront of innovation.

Thought Leadership

Speak to us about starting your Data and Analytics journey today!