Today, data is everywhere: on premise, mobile, and in the cloud. As a business grows, so do the quantity and complexity of data. The need is to uncover new and meaningful patterns in your collected data to make informed business decisions, improve processes and enhance customer satisfaction.
Zrima provides data mining outsourcing services to help organizations convert raw data into actionable insights. Our outsourced data mining services experts analyze large volumes of data stored in your data warehouse using pattern recognition technologies and statistical and mathematical modelling algorithms. This enables us to reveal hidden patterns in your data that can’t be detected using standard OLAP and query tools. With a broad set of data mining capabilities and well-defined operational frameworks, we help organizations maximize the value of all data and assess future business prospects with confidence
Data mining, also known as Knowledge Discovery in Databases (KDD), is an automated process to extract valuable insight from large data sets that can be essential in the decision-making process. At Zrima, we leverage cross-industry standard process for data mining (CRISP-DM) to help our clients make the most of their enterprise data. Our data mining process consists of the following stages:
We treat every single data mining project as a unique venture and offer custom solutions to meet your specific business requirements. Our in-depth knowledge on data mining processes coupled with advanced techniques make us the preferred choice for data mining needs in many industries including retail, manufacturing, insurance, telecom, banking, e-commerce, hospitality, and more. We help organizations make informed business decisions with our data mining outsourcing services consisting of the following
| Data extraction from scanned documents | Pre-processing of data from your warehouse | Extracting meta-data from websites | Gathering data from websites to excel spreadsheets | Information collection from social media websites | Data mining for fraud detection | Online news and information research | Spreadsheet presentations of extracted data | Online synchronization for different databases | Service, product, and brand feedback search | Analysis and interpretation of industry data | Competitors’ growth analysis and tracking |