Thealmit

Services

Enterprise Services

The solutions from almIT are made to assist you in providing your users with significant value. We are aware of how technology affects business users’ productivity. Our mission is to take use of new and existing technology to develop products that serve as catalysts for increased business efficiency. With almIT, you can provide your users:

  • Quicker access to reliable, essential information.
  • Integrating line of business applications seamlessly to maintain critical context.
  • Improved productivity and integrated presence through communications and collaboration solutions.
  • Programs with a rich user interface that excel at data processing and representation.
Enterprise Services

ENTERPRISE APPLICATION INTEGRATION (EAI)

Supply chain management, which governs inventory and shipping, customer relationship management (CRM), business intelligence (BI), which identifies patterns in operational data, and other data management applications, such as internal communications, health care, and human resources, are just a few examples of today’s industries that typically cannot communicate with one another to share data or analytics and business intelligence practices, rules, etc. If these applications cannot communicate effectively and effectively, they will be ineffective. Our main pursuits in putting EAI into practice were:

 

Bus/Hub: Typically, this improves middleware, such as an application server or message bus.

 

Connectivity: Through a group of adapters, the bus/hub connects applications (Connectors). We use adapters to interact between the apps since they are crucial to application integration, which outlines the how (protocol), what (data type), and communication direction (one-way and two-way) as well as access level, among other things. We ensure that these adapters will adhere to the security standards of each unique application taking part in integration.

 

Schema Validation and Transformation: We evaluate each message’s compliance with the application it is communicating with to prevent the use of inconsistent data and incorrect data formats. The data is transformed using transformations into an application format for a bus? a standard format. To share the data with other applications appropriately, we add semantic changes to it.

 

Integration Module: Each form of integration is handled by a particular integration module, and an EAI system may be taking part in numerous concurrent integration processes at any given moment. Modules for integration subscribe to certain sorts of events and process notifications they get when these events happen. We list every integration module separately, along with the events it triggers, the recipients of its notifications, etc. To calculate the number of dependencies between integration modules, we shall count them.

 

Support of Transactions: The transactions in application integration are distinct from one another. All of the applications must support the transactions. We use distributed transaction controllers by implementing two-phase commit protocols or compensating transactions.

Cloud Services

Cloud Computing

Cloud Computing

Businesses of all sizes, from small to large, spend the majority of their budgets on IT infrastructure. If we look at their yearly spending, the majority of it is for on-premise expenses. Cloud Optimization in Cost Management is another aspect where you can save money.

Infrastructure Migration

Assessment & Planning Adopting target Cloud Adoption Framework to assess the existing data center VMWare or Hyper-V workloads and plan an efficient target cloud infrastructure. In this stage, we identify workload dependency, network requirements, security, storage & encryption requirements.

Feasibility Study Performance, Operational, and Financial Feasibility Study will be conducted and documented to get approvals from the Product Owners and Stakeholders

Phase-wise Migration We will carry out phase-wise migration from the lowest dependency workload footprint to the complex with all requirements identified in the assessment and planning stage.

Monitoring Postmigration, we will review the health, and performance sustainability monitoring to make sure workloads are delivering the expected results.

Platform Migration

Architecture Review Reviewing the existing application architecture, and non-functional requirements by components, development framework, layers, network protocols, encryption, and storage requirements. We will identify how we can migrate existing legacy components to modernized cloud components.

Feasibility Study We review adherence to Capacity Planning, Non-functional requirements, and Performance and come up with a Feasibility study in the Financial and Execution Plan. This will help Business Owners to decide on full or partial migration to start with.

Phase-wise Implementation We will pick easy and isolated components to be migrated first, then medium and complex. Each component will be rewritten or improved depending on the degree of migration required as per the assessment and planning.

Operations (DevOps) For every app/service we will develop CI/CD Pipelines for rapid build and deployment.

Quality Assurance Functional and Performance Tests will be executed on all components to make sure SLAs are covered and not degraded.

Monitoring All operations are monitored for proactive steps to be taken and take advantage of identifying performance issues upfront. This will improve business continuity and reduce downtime.

Enforcing Security at various levels

  • Implementing best Security Practices at various levels to secure Data, Applications, Cloud-Infrastructure.
  • Data Security – Securing Data at rest and Transit with best encryption practices.
  • Application Security – Policy Control, Connectors, Discovery, Proxy Access + Session.

Enterprise Data Integration

  • Implementing EDI utilizing Cloud Service Bus components viz., Enterprise Messaging, Messaging Workflows, Enterprise Event Management, App Services, and Functions.

Type of Migration Services We Offer

  • Data Center Migration
  • Hybrid Cloud Migration
  • Cloud-to-Cloud Migration
  • Apps and Database Migration

IoT Services

We provide IoT services in all phases of the IoT Lifecycle in modeling, designing, building, provisioning, deploying, and operating them for any size of the industry.

Device Onboarding

Security:
Authorized device Connectivity with an IoT System is very important, otherwise, counterfeit devices are ready to exchange communication. So the following steps are very important:

  • X.509 Certificates, TPM-based identity attestation
  • Managing Enrollment List, for the desired devices or group of devices
  • Encryption – Data at rest will be encrypted using 256-bit AES encryption.
  • Monitoring – By logging all the milestones, we will make sure everything is captured for frequent monitoring.
Performance:
  • Allocation Policy – Having a custom allocation policy that suits to the target industry, to make sure devices are balanced with IoT Hubs.
  • Cross-Region – Depending upon the device location, we will provision them to the appropriate IoT Hub in same region.
Challenge

The biggest Challenge is the Quota Limits from the Service Providers. There are millions of devices, but quotas have to be utilized smartly to provision. Multiple Provisioning Services across Multiple IoT Hubs bring the capability to match the volumes. Depending upon the number of devices operate in the system, we will design allocation policy to provision devices to the IoT System.

Digital Twins

Digital Twins is a platform as a service (PaaS) offering that enables the creation of twin graphs based on digital models of entire environments, which could be buildings, factories, farms, energy networks, railways, stadiums, and more—even entire cities. These digital models can be used to gain insights that drive better products, optimized operations, reduced costs, and breakthrough customer experiences.

Digital Twins can be used to design a digital twin architecture that represents actual IoT devices in a wider cloud solution, and which connects to IoT Hub device twins to send and receive live data.

We Define Your Digital Business:

We will identify and define all digital entities that are part of the IoT System viz., people, places, and machines in your physical environment We will identify your business data models and convert them to digital twins. 

 

 

Digital Twins Data Maturity

All devices that are connected to IoT Systems, and services like REST APIs, and Logic APIs can contribute the data to the Digital Twin Data Model.  This data is immediately available for querying to all the cloud services. This data can be used in visualization dashboards.

Visualization Tools

We will develop dashboards that will help business owners and technical teams to look into actual insight into the existing system as is. This will help you to make necessary proactive decisions. These dashboards show the current live stream data from the Digital Twins Data Store.

IoT Backend Services

Backend Processing:

IoT Services are not only connecting your edge devices to a central system, there are lot of data it is emitting or collecting. This data might trigger a lot of services to manage the accurate state or events on other subsystems. We develop the full lifecycle of your IoT Requirement from Device Onboarding to Visualization Boards. 

Security:

         Protect your organization on all fronts; hardware, software, and cloud. We will make sure that; the data is secured in transit and rest, from chip to cloud. It will be accessible to only authorized roles in your organization.

           

Cloud Partners:

Our major cloud platform solutions are using Microsoft Azure and Amazon Web Services (AWS)

Data & AI

“At ALMIT, we specialize in transforming businesses through advanced AI and IoT solutions. Our services are designed to navigate the complexities of digital transformation, offering bespoke strategies and cutting-edge technological integration. From AI-driven insights to robust IoT ecosystems, we focus on delivering practical and innovative solutions. Our core services include AI Strategy & Advisory, IoT Solutions, Data Analytics & Engineering, Machine Learning & AI, and Operational Insights. Each service is tailored to empower your business with data-driven decision-making and operational efficiency. Explore our services to find the perfect solution for your unique business challenges.”

Services Offered: Data/AI Solutions Implementaion & Advisory:

“At ALMIT, our AI Strategy & Advisory service goes beyond conventional consulting. Our team of seasoned AI strategists collaborates closely with your organization to craft a tailor-made AI roadmap that aligns perfectly with your business goals. With a deep understanding of AI’s transformative potential, we assess your current technological landscape, ensuring a seamless integration of AI solutions. Our unique approach combines industry expertise with cutting-edge technology, delivering a roadmap that not only identifies opportunities but also outlines practical steps to harness AI’s full potential.”

1. IoT Solutions:

“ALMIT specializes in IoT Solutions that are as unique as your business. Our team’s expertise in designing, implementing, and managing IoT systems is unparalleled. We believe in IoT solutions that are customized to meet your industry’s specific needs. By ensuring reliable data collection, efficient processing, and robust data security, we create IoT ecosystems that empower your business. What sets us apart is our commitment to scalability, interoperability, and the security of your IoT infrastructure, providing you with a trusted partner for driving innovation through IoT.”

2. Data Analytics & Engineering:

“Data is at the heart of your business, and at ALMIT, our Data Analytics & Engineering service ensures your data is your greatest asset. Our team specializes in advanced data processing, analytics, and engineering solutions that are not only powerful but also uniquely tailored to your business. We employ the latest technologies to handle big data and real-time analytics, making your data accessible and actionable. All seamlessly integrated with data lake and Lakehouse architectures. With ALMIT, you have a partner that transforms data into insights, enabling you to make informed decisions and stay ahead in your industry.”

Cloud Computing

3. Machine Learning & AI:

“ALMIT’s Machine Learning & AI service embodies innovation. Our team excels in developing custom machine learning models that are the perfect fit for your business challenges. What sets us apart is our commitment to creating solutions that scale seamlessly and remain sustainable. We leverage cutting-edge technologies and frameworks to ensure your business stays ahead in the ever-evolving world of AI. At ALMIT, we don’t just build models; we build the future of your business.”

4. Analytics & Operational Insights:

“Turning data into operational excellence is our promise at ALMIT. Our Operational Insights service equips your organization with the tools and techniques to extract actionable insights from your data. We empower data-driven decision-making across your business, thanks to our team’s expertise in data visualization and advanced reporting. ALMIT transforms complex data sets into clear, actionable information, driving operational efficiency and propelling your business towards success.”

Cloud computing security abstract concept vector illustration. Cloud information security system, data protection service, safety architecture, network computing, storage access abstract metaphor.
SaaS technology abstract concept vector illustration. Software as a service, cloud computing, application service, customer access, software licensing, subscription, pricing abstract metaphor.

5. GenAI-Powered Transformation:

“At ALMIT, our genAI-powered support transformation service focuses on revolutionizing the support industry. From Proof of Concept (POC) to full-scale implementation, we harness the potential of genAI solutions to streamline operations, reduce manual efforts, and enhance customer support efficiency. Our expertise extends to designing intelligent chatbots and implementing automation workflows, making ALMIT your trusted partner for genAI-driven support transformation.”

Consulting

In every area of business services, each organization must compete with its business rival. As a means of competing against its main rivals and gaining client satisfaction. Every business should also compete with its rival in all facets of business services. It must have the best information technology infrastructure to win customer satisfaction and compete with its core competitors. almIT will assist organizations in focusing on IT Vision, developing processes, and implementing them.

 

 

With the support of case studies, almIT assists enterprises as a partner in each discrete cardinal point of the entire development life cycle by arriving at agreed needs that will ease the business process. User interviews generate business cases, architectures, resource plans, implementation, training, and help catalogs, all of which lead to a successful business.

 

We collaborate with the client to produce remarkable and long-term improvements in quality, cost efficiency, and operational flexibility. Allowing for speedier time-to-market and more innovation effectiveness. Based on industry and customer measurements and insights, we establish end-to-end process performance.

Staffing

almIT offers unique and smart staffing solutions. We provide a full-service staffing solution to suit your ever-changing technological demands while also providing the greatest degree of customer satisfaction.

We are a global IT solutions and engineering services employment firm. To achieve an excellent match, we employ a strict hiring, grooming, and deployment process that includes technical testing and numerous rounds of interviews. Our placement approach is objective, fair, and centered on the needs of our customers. After you have determined the precise needs of your company, you will be provided with candidates who are the finest in that field.

almIT also offers a changeable staffing solution to meet occasional needs or numerous engagements running concurrently. This enables an economical team structure, as well as recruiting knowledgeable people in the shortest period of time and reducing team size as needed.

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Case Study 1 : Revolutionizing Manufacturing Operations with Azure IoT Digital Twin


Client Overview:

  • Client Name: TechFab Manufacturing Solutions
  • Industry: Manufacturing
  • Location: Springfield, USA
  • Size: Medium-Scale Manufacturing Facility

Problem Statement: TechFab Manufacturing Solutions, a leading player in the manufacturing industry, faced challenges related to inefficient machinery maintenance and equipment downtime. Their existing maintenance processes were primarily reactive, leading to unexpected production interruptions, increased costs, and reduced overall equipment effectiveness (OEE). They sought a proactive solution to optimize manufacturing operations.

Solution:

  • ALMIT's team of Azure-certified architects and IoT specialists collaborated with TechFab to design a comprehensive solution.
  • The core of the solution was the implementation of Azure IoT Digital Twin technology, which created virtual representations of physical manufacturing equipment and processes.
  • A network of IoT sensors, including Microsoft Azure IoT Hub, was deployed across critical machinery to continuously collect real-time data on machine health, performance, and environmental conditions.
  • Data from sensors was transmitted securely to Azure IoT Hub for processing and analysis.
  • Azure IoT Central was used to manage and monitor IoT devices, providing a centralized platform for device management and monitoring.

Understanding Azure IoT Digital Twin: A Digital Twin is a virtual representation of a physical object, process, or system. In the context of manufacturing, it means creating a detailed digital replica of manufacturing equipment and processes. This virtual twin is kept in sync with its physical counterpart in real-time, thanks to data from IoT sensors. It allows for:

  • Real-time Monitoring: Engineers can monitor the digital twin to gain insights into the physical equipment's status, health, and performance.
  • Predictive Maintenance: By analyzing historical and real-time data, machine learning models can predict when equipment is likely to fail, enabling proactive maintenance.
  • Simulation and Optimization: Digital Twins can be used to simulate different scenarios, helping optimize processes and improve efficiency.

Implementation:

  • Azure IoT Digital Twins: The ALMIT team configured Azure IoT Digital Twins to mirror the physical equipment, providing a real-time digital replica that allowed for advanced analytics and predictive maintenance.
  • Azure IoT Hub: Data from IoT sensors was securely transmitted to Azure IoT Hub, where it underwent real-time processing, transformation, and analysis.
  • Machine Learning: Advanced machine learning algorithms were employed to predict equipment failures based on historical data and real-time sensor information.
  • Power BI Dashboard: ALMIT created a custom Power BI dashboard for TechFab, providing engineers with a user-friendly interface to monitor equipment health, receive alerts, and plan maintenance proactively.

Solution Diagram:

Results:

  • TechFab Manufacturing Solutions experienced significant improvements in manufacturing operations:
    • Equipment downtime was reduced by 30% due to predictive maintenance.
    • Overall Equipment Effectiveness (OEE) increased by 15%.
    • Energy consumption was optimized, resulting in a 20% reduction in energy costs.
    • Production efficiency improved, leading to a 10% increase in output.
    • Maintenance costs decreased by 25%, as resources were allocated more efficiently.

Client Testimonial: "ALMIT's implementation of Azure IoT Digital Twins transformed our manufacturing operations. We now have a proactive approach to maintenance, reducing downtime and costs significantly. The digital twin technology provides invaluable insights into our equipment's health, and the user-friendly Power BI dashboard keeps our engineers informed and in control. We couldn't be happier with the results." - John Smith, COO, TechFab Manufacturing Solutions.

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Case Study 2 : Azure Lakehouse Implementation at FinTech Solutions


Client Overview:

  • Client Name: FinTech Solutions
  • Industry: Financial Services
  • Location: New York City, USA
  • Size: Mid-Sized FinTech Company

Problem Statement: FinTech Solutions was grappling with significant data management challenges due to siloed data storage systems. This resulted in inefficient data processing, delayed analytics, and compliance issues. They needed a unified data platform to enhance decision-making, ensure regulatory compliance, and facilitate advanced analytics and real-time data streaming.

Solution: ALMIT, leveraging its team of Azure-certified architects and data lake specialists, collaborated with FinTech Solutions to develop a comprehensive solution centered around Azure Lakehouse architecture. This approach combined data lake and data warehouse features to provide unified data storage, processing, analytics, reporting, and real-time streaming. Key components included:

  • Azure Data Lake Storage: Centralized repository for structured and unstructured data.
  • Azure Databricks: Employed for data processing and transformation, ensuring data quality and consistency.
  • Azure Synapse Analytics: Unified layer for analytics and reporting, enabling scalable data querying.
  • Azure Stream Analytics: Integrated for real-time data streaming and processing.

Understanding Azure Lakehouse Solution: Azure Lakehouse is a hybrid solution that merges the capabilities of a data lake and a data warehouse. It stores large volumes of raw data (data lake) and offers the structure and speed for advanced analytics, reporting, and real-time streaming (data warehouse).

Implementation:

  • Data Integration: All data sources were integrated into Azure Data Lake Storage.
  • Data Processing: Handled by Azure Databricks for quality and consistency.
  • Analytics and Reporting: Azure Synapse Analytics provided scalable querying and BI.
  • Real-time Streaming: Achieved through Azure Stream Analytics.

Advanced Analytics Component: The solution empowered FinTech Solutions with advanced analytics capabilities, including predictive modeling, machine learning, and real-time streaming analytics.

Data Volume: Designed to manage terabytes of financial data, including transactions, market data, and customer information, the Azure Lakehouse solution ensures scalability with growing data volumes.

Solution:

Results:

  • Data Processing: 40% reduction in processing time.
  • Compliance: Streamlined processes reducing regulatory risks.
  • Data Quality: Enhanced reliability through improved data consistency.
  • Scalability: Architecture capable of handling terabytes of data and real-time streaming.

Client Testimonial: Sarah Johnson, CTO of FinTech Solutions, lauded the implementation, noting significant improvements in data management, analytics, and real-time capabilities. The unified platform provided the flexibility of a data lake with the speed of a data warehouse, improving processing times, compliance, and advanced analytics capabilities.

Conclusion: This case study exemplifies how ALMIT's Azure Lakehouse solutions can revolutionize data management, compliance, advanced analytics, and real-time streaming in the financial services sector, managing substantial data volumes for data-driven decision-making.

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Case Study 3: ALMIT's AI-Powered Audio Prognostics and Diagnostics for MechanoTech Industries


Client Overview:

  • Client Name: MechanoTech Industries
  • Industry: Manufacturing and Equipment Maintenance
  • Location: Stuttgart, Germany
  • Size: Large Manufacturing Company

Problem Statement: MechanoTech Industries, renowned in the field of industrial equipment manufacturing and maintenance, faced critical challenges in predictive maintenance and fault diagnosis. Conventional methods were proving inadequate, leading to extended equipment downtime and increased repair costs. The company sought an advanced solution to enhance its ability to predict equipment failures and accurately diagnose issues in a timely manner.

Solution: ALMIT, known for its expertise in AI and machine learning, collaborated with MechanoTech Industries to develop an innovative audio-based prognostics and diagnostics system. The solution incorporated:

  • Audio Sensing Devices: Installation of sophisticated audio sensors on critical equipment to capture distinct sound signatures.
  • AI-Driven Machine Learning Models: Development of AI algorithms trained to detect and interpret patterns in audio data, correlating them with specific equipment conditions.
  • Real-Time Audio Monitoring: A system for continuous monitoring and real-time analysis of audio data from equipment.
  • Advanced Diagnostic Software: A software platform designed to analyze the audio data and provide diagnostic and prognostic insights.

Implementation:

  • Retrofitting Equipment: Strategic placement of audio sensors on essential equipment for comprehensive sound capture.
  • Continuous Data Harvesting: Implementing a system for the ongoing collection and processing of audio data.
  • AI-Powered Analysis: Utilizing machine learning to identify standard operational sounds and anomalies indicating potential mechanical issues.
  • Intuitive Diagnostic Dashboard: Creating a user-friendly interface for maintenance personnel to receive alerts and detailed diagnostics.

Azure Solution Stack:

  • Azure IoT Edge Devices: Representing the audio sensors installed on the equipment for capturing sound data.
  • Azure IoT Hub: The central point for aggregating audio data from IoT devices.
  • Azure Stream Analytics: Processing real-time audio data streams.
  • Azure AI Services (Cognitive Services/Azure Machine Learning): Analyzing audio data for pattern recognition and anomaly detection.
  • Azure Data Lake Storage: Storing processed and raw audio data.
  • Azure Synapse Analytics: Integrating data storage with advanced analytics.
  • User Interface/Application: A dashboard for maintenance technicians to receive alerts and diagnostics.

Results:

  • Decreased Downtime: Proactive detection of potential issues led to a substantial reduction in equipment downtime.
  • Cost Efficiency: Predictive maintenance guided by precise diagnostics resulted in lowered repair expenses.
  • Operational Efficiency: Maintenance teams were able to swiftly identify and resolve equipment issues, enhancing overall efficiency.
  • Innovation in Maintenance: MechanoTech Industries established itself as a pioneer in the field of advanced equipment maintenance through this implementation.

Client Testimonial: "With ALMIT's AI-powered audio diagnostic technology, we've fundamentally transformed our maintenance operations. Our equipment downtime has significantly decreased, and our maintenance costs have been reduced dramatically. The accuracy and speed with which our technicians can now diagnose and resolve issues are unparalleled." - Dr. Hans Becker, CEO, MechanoTech Industries.

This case study exemplifies how ALMIT's innovative AI-driven audio prognostics and diagnostics solution enabled MechanoTech Industries to revolutionize its approach to equipment maintenance, setting a new benchmark in predictive maintenance and diagnostics within the industry.

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Case Study 4 : Revolutionizing Retail Analytics with Azure Lakehouse Integration & LLM


Client Overview:

Client Name: MarketEdge Retailers

Location: Chicago, USA

Size: Large Retail Company

Problem Statement:

MarketEdge Retailers, a prominent entity in the retail sector, encountered operational inefficiencies and data integration challenges due to their reliance on an outdated on-premise SAP system and fragmented data from various third-party sources like Google Analytics. The key issues included inefficient data handling, limited analytics capabilities, and delays in accessing real-time customer insights. To address these challenges, MarketEdge Retailers required an innovative data management system that could integrate multiple data sources into a single, efficient platform, essential for enhancing decision-making processes, customer experience, and overall operational efficiency.

Solution:

ALMIT's team, composed of Azure-certified specialists and data migration experts, crafted a custom solution for MarketEdge Retailers. This solution entailed a migration from their existing on-premise SAP system to a more sophisticated Azure Lakehouse architecture, effectively unifying their data management and analytics systems.

A pivotal element of this solution was the integration of Azure OpenAI and Databricks, empowering end-users to interact with data through natural language processing (NLP), thus bypassing traditional dashboard-based analytics.

Unique Implementation Details:

  • Azure Lakehouse Framework: A central Azure Data Lake Storage was established, integrating data from both SAP and third-party applications like Google Analytics. This setup offered the benefits of both data lake and data warehouse, ideal for storing large volumes of raw data and facilitating structured data queries for advanced analytics.
  • Azure Databricks: Managed efficient data processing and transformation, maintaining high-quality and consistent data for analytics. It also enabled machine learning and AI functionalities.
  • Azure OpenAI and Databricks Integration: This integration allowed MarketEdge Retailers to use large language models (LLMs) for intuitive data interaction. Users could input natural language queries, which were then translated into data processing tasks by Databricks, democratizing data analytics for non-technical users.
  • Azure Synapse Analytics with Self-Hosted Native SAP ECC Connector: Azure Synapse Analytics was deployed with a self-hosted native SAP ECC connector. This allowed for seamless integration and extraction of data from the SAP ECC system, significantly improving the efficiency and reliability of data transfers.
  • Estimated Savings with SAP BW Module Replacement: By leveraging Azure Synapse Analytics and its SAP ECC connector, MarketEdge Retailers could potentially save millions in software and hardware costs associated with their traditional SAP BW module. This was a major financial benefit, as it streamlined their data warehouse operations and reduced reliance on expensive, proprietary SAP hardware and software.

Results with Metrics:

  • Data to Insights Time Reduction: The transition from data to insights was cut down from weeks or months to minutes, drastically speeding up decision-making processes.
  • Significant Cost Savings: Estimated savings in the millions due to the replacement of the SAP BW module with Azure Synapse Analytics, reducing both software and hardware expenses.
  • Enhanced Real-Time Data Analysis: Improvement in real-time data analysis capabilities by 40%, enabling quicker responses to market trends and customer behavior.
  • Increased Data Interaction by Non-Technical Staff: A 70% rise in data interaction by non-technical staff, indicating improved accessibility and user-friendliness.
  • Reduced Dashboard Development Time: A 60% reduction in the time required for developing and maintaining dashboards.

Client Testimonial:

“The collaboration with ALMIT and the subsequent implementation of the Azure Lakehouse solution, complete with Azure OpenAI and Databricks, has been transformational. The integration of Azure Synapse Analytics with a self-hosted native SAP ECC connector has not only streamlined our data processes but also led to significant financial savings by replacing our traditional SAP BW module. This technological advancement has rapidly accelerated our data-to-insight journey, transforming our decision-making process and enhancing our competitive edge in the retail market.” - Alex Thompson, CIO, MarketEdge Retailers.

This case study highlights ALMIT's skill in deploying Azure Lakehouse solutions, augmented with Azure OpenAI, Databricks, and a specialized Azure Synapse Analytics SAP connector, to significantly enhance data management and analytics for MarketEdge Retailers. This strategy has streamlined operations, provided substantial cost savings, and improved data accessibility and decision-making speed in the retail sector.

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