Dynamic Image Group has worked with multiple industries to provide solutions that help improve business processes, workflow, customer relations, workforce efficiency and improving profit margins. DIG has the understanding of multiple programming languages from Windows based or Unix based systems.
DIG solutions can work with the standard off the shelf packages. Our specialty is to provide customers with choices outside of the traditional commercial or proprietary applications like SAP, Oracle, Salesforce and Microsoft. For companies seeking increased solutions control to accommodate challenging industry requirements, unique business processes, complex feature sets or budgetary constraints, DUG software can provide both a viable alternative and an entry point to an enterprise-wide solutions technology strategy.
Enterprise resource planning (ERP) solution is a business management software—usually a suite of integrated applications that a company can use to collect, store, manage and interpret data from many business activities, including and note limited to:
- Product planning, cost
- Manufacturing or service delivery
- Marketing and sales
- Inventory management
- Shipping and payment
- Resource management
ERP provides an integrated view of core business processes, often in real-time, ERP systems track business resources cash, raw materials, production capacity and the status of business commitments: orders, purchase orders, and payroll. The applications that make up the system share data across the various departments (manufacturing, purchasing, sales, accounting, etc.) that provide the data. ERP facilitates information flow between all business functions, and manages connections to outside stakeholders.
Customer relationship management (CRM) is a system for managing a company’s interactions with current and future customers. It often involves using technology to organize, automate and synchronize sales, marketing, customer service, and technical support.
CRM Solutions come with many features and tools that are important for our clients based on their specific organizational needs. These are just a few of the functions DIG provides with its CRM Solutions:
Relationship management is a customer-oriented feature with service response based on customer input, one-to-one solutions to customers’ requirements, direct online communications with customer and customer service centers that help customers solve their issues.
Sales force automation can implement sales promotion analysis, automate tracking of a client’s account history for repeated sales or future sales, and also coordinate sales, marketing, call centers, and retail outlets in order to realize the salesforce automation.
Use of technology is about following the technology trend and skills of value delivering using technology to make “up-to-the-second” customer data available. It applies data warehouse technology in order to aggregate transaction information, to merge the information with CRM solutions, and to provide KPI (key performance indicators).
Opportunity management helps our clients to manage unpredictable growth and demand and implement a good forecasting model to integrate sales history with sales projections.
Marketing and Customer Service track and measure marketing campaigns over multiple networks. Our solutions can track customer analysis by customer clicks and sales. Places where CRM is used include call centers, social media, direct mail, data storage files, banks, and customer data queries.
Data mining (the analysis step of the "Knowledge Discovery in Databases" process), an interdisciplinary sub field of computer science,is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.
DIG Data Mining solutions have helped clients make business decision that are ahead or the curve. We have collected data from social networks, news feeds and our clients business systems to be restructured and presented for analyses.
The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection) and dependencies (association rule mining). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting are part of the data mining step, but do belong to the overall KDD process as additional steps.