HRIS Solutions
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Technology has created countless advances that help today's businesses thrive. One of the best technological additions to your company is human resource software. There are many different reasons to add human resource software to your company including higher productivity, fewer errors, and easier access to data. But choosing human resource software can be difficult since so many different products are on the market today. With so many choices, you may have a hard time narrowing them down to the one that works best for you
  • Employee Management
  • Payroll
  • Integration with Attendance devices
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  • Learning and Exam Dumps
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TIME AND ATTENDANCE SOFTWARE FEATURES
att
Flexible, convenient, accurate, and integration with multiple Attendance devices i.e. Barcode, Biometric, RFID, Face Reader etc Attendance will help you get workforce management into shape. Our software is designed to effectively manage many difficult scheduling issues, like remote workers, drivers, distributed teams, and more. 
We simplify the complicated world of scheduling, leave requests, and reporting while helping you maintain compliance in a rapidly changing world. Here are a few features of our Time and Attendance software:

  • Business rule-based options.
  • Multi-level, user-defined business policies.
  • Eliminates the need for timecards with PC/mobile/biometric options and more.
  • Electronic timecard management.
  • Unlimited user-defined scheduling.
  • Broad selection of standard reports.
MANUFACTURING ERP
erp
END TO END Manufacturing cycle in user friendly interface. The functionality of manufacturing software varies based on the industry focus and the production process utilized. Most ERP and manufacturing solutions are placed into the categories of process manufacturing software, discrete manufacturing software, or mixed-mode manufacturing software. These different manufacturing categories directly relate to the production environment and whether this environment can be classified as continuous process, contract manufacturing, job shop, batch processing, repair and maintenance, repetitive, or work order based.
Some key features :

  • END to END Operational Activity.
  • Financial Reporting.
  • Administration module.
  • Payroll.
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SMALL FINANCIAL SOLUTION
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Are you having trouble moving from manual processes to a more transparent, automated portfolio analysis? Our software solution automates processes, enables compliance with changing regulations, and prepares you with accurate data analysis that improves real-time decision-making to enhance your bottom line.

Small business accounting software is the best way to record and manage the daily sales and purchase activities of any company. Application has a full control over the invoicing and inventory system of your business. Accounting information system can generate financial reports in several forms like inventory reports, sales reports, purchasing reports, ledger reports, company expenses reports and party reports. Billing management program can calculate ...

INVENTORY SOLUTIONS
ext
Inventory control solution that lets you track tens of thousands of parts and products in multiple warehouses. It is the best choice for small and midsize businesses because of its seamless integration with Barcode, flexible feature set, and enormous library of training and support resources.

Inventory System is designed to handle every aspect of inventory management, providing the ability to track each step in the inventory life cycle from the time you create a purchase order for your supplier to the moment you ship the product to your customer. At the same time, Inventory Control System’s modular organization ensures flexibility and enables you to adapt the program to your specific needs. 

Having Multiple inventory solution :

  • Auto Parts solution.
  • General Inventory.
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  • FIFO, LIFO, Average Costing Method.

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Exam Number : Google-PDE
Exam Name : Professional Data Engineer on Google Cloud Platform
Vendor Name : Google
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A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

The Professional Data Engineer test assesses your ability to:
- Design data processing systems
- Build and operationalize data processing systems
- Operationalize machine learning models
- Ensure solution quality

1. Designing data processing systems
1.1 Selecting the appropriate storage technologies. Considerations include:
- Mapping storage systems to business requirements
- Data modeling
- Tradeoffs involving latency, throughput, transactions
- Distributed systems
- Schema design

1.2 Designing data pipelines. Considerations include:
- Data publishing and visualization (e.g., BigQuery)
- Batch and streaming data (e.g., Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
- Online (interactive) vs. batch predictions
- Job automation and orchestration (e.g., Cloud Composer)

1.3 Designing a data processing solution. Considerations include:
- Choice of infrastructure
- System availability and fault tolerance
- Use of distributed systems
- Capacity planning
- Hybrid cloud and edge computing
- Architecture options (e.g., message brokers, message queues, middleware, service-oriented architecture, serverless functions)
- At least once, in-order, and exactly once, etc., event processing

1.4 Migrating data warehousing and data processing. Considerations include:
- Awareness of current state and how to migrate a design to a future state
- Migrating from on-premises to cloud (Data Transfer Service, Transfer Appliance, Cloud Networking)
- Validating a migration

2. Building and operationalizing data processing systems
2.1 Building and operationalizing storage systems. Considerations include:
- Effective use of managed services (Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore)
- Storage costs and performance
- Lifecycle management of data

2.2 Building and operationalizing pipelines. Considerations include:
- Data cleansing
- Batch and streaming
- Transformation
- Data acquisition and import
- Integrating with new data sources

2.3 Building and operationalizing processing infrastructure. Considerations include:
- Provisioning resources
- Monitoring pipelines
- Adjusting pipelines
- Testing and quality control

3. Operationalizing machine learning models
3.1 Leveraging pre-built ML models as a service. Considerations include:
- ML APIs (e.g., Vision API, Speech API)
- Customizing ML APIs (e.g., AutoML Vision, Auto ML text)
- Conversational experiences (e.g., Dialogflow)

3.2 Deploying an ML pipeline. Considerations include:
- Ingesting appropriate data
- Retraining of machine learning models (Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML)
- Continuous evaluation

3.3 Choosing the appropriate training and serving infrastructure. Considerations include:
- Distributed vs. single machine
- Use of edge compute
- Hardware accelerators (e.g., GPU, TPU)

3.4 Measuring, monitoring, and troubleshooting machine learning models. Considerations include:
- Machine learning terminology (e.g., features, labels, models, regression, classification, recommendation, supervised and unsupervised learning, evaluation metrics)
- Impact of dependencies of machine learning models
- Common sources of error (e.g., assumptions about data)

4. Ensuring solution quality
4.1 Designing for security and compliance. Considerations include:
- Identity and access management (e.g., Cloud IAM)
- Data security (encryption, key management)
- Ensuring privacy (e.g., Data Loss Prevention API)
- Legal compliance (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children's Online Privacy Protection Act (COPPA), FedRAMP, General Data Protection Regulation (GDPR))

4.2 Ensuring scalability and efficiency. Considerations include:
- Building and running test suites
- Pipeline monitoring (e.g., Stackdriver)
- Assessing, troubleshooting, and improving data representations and data processing infrastructure
- Resizing and autoscaling resources

4.3 Ensuring reliability and fidelity. Considerations include:
- Performing data preparation and quality control (e.g., Cloud Dataprep)
- Verification and monitoring
- Planning, executing, and stress testing data recovery (fault tolerance, rerunning failed jobs, performing retrospective re-analysis)
- Choosing between ACID, idempotent, eventually consistent requirements

4.4 Ensuring flexibility and portability. Considerations include:
- Mapping to current and future business requirements
- Designing for data and application portability (e.g., multi-cloud, data residency requirements)
- Data staging, cataloging, and discovery



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RETAIL POINT OF SALE (POS)
POS.jpg
Retail store owners operate on tight margins, and have many constantly moving parts. This becomes especially difficult to manage efficiently when using manual methods. A point-of-sale system is a great tool to manage all these moving parts while helping to ensure customer satisfaction, but finding the right POS for small business is no easy feat.

POS can help businesses in a variety of ways, including managing inventory, providing customer management data, identifying opportunities and weaknesses in the store and much, much more.

EMBRIODRY MANAGMENT SOLUTION
machine.jpg
Embroidery’s Industries can utilize this embroidery management tool in a wide variety of ways which will insure that jobs are scheduled, processed, and delivered on time and with the maximum efficiency. This embroidery management software was developed with your business in mind - whether it be big or small - and can be customized to any unique needs you may have.

You may be a business owner or one of the project managers in an embroidery department, our embroidery management software will take the stress out of organizing and coordinating the activities of both you and your clients. An embroidery business can benefit greatly from embroidery management systems that offer ways to harmonize and coordinate multiple departments. To accomplish this, the embroidery management systems are integrated to allow the user to track various job control systems which may incorporate multiple program management structures.

Embroidery Management Capabilities:
  • Covering all Operational Activity.
  • Financial Reporting.
  • Employee Management.
  • Payroll.
  • Stiched wise Billing.
  • Invoicing.
HOSPITAL SOLUTION
medical
It is a complete enterprise management solution that streamlines clinical, administrative, and financial operations of care delivery organizations, providing unprecedented opportunities for productivity, collaboration, and growth.

Whether your goal is to enhance the value of services to your patients, increase reimbursements, improve the overall efficiency of day-to-day operations, or simply stay ahead of compliance requirements,

  • Patient Management System.
  • Doctor Management System.
  • Drugs Management System.
  • Administrative Rights Management System.
  • Online Appointment Management System.
  • Patient Payment System.
  • Medical Services System.
  • Doctor Services Report System.
  • Pharmacy (Medicine) Management System.
  • Lab Test System.