Building Database - Market Advantage
We build custom database solutions for any business verticals. We provide the most up to date data to business solutions which helps them to make strategies. Our database is centralized and easy to use, we offer custom headers for any database solutions that make it easy to implement for any business. Success depends on the ability to accurately answer a variety of questions related to your business and industry. Sometimes it becomes very tough to get access to that information, there we come into the picture. Our data mining team is specialized in acquiring, analyzing, and enriching data, as well as converting it into business intelligence.
Methods of Data Mining:
Primary Research: Our primary research team is well equipped with industry research experience in data mining which helps us to serve our clients without any question. Primary research is an effective method of data mining to extract key information through calling. It also helps in data validation gathered through various modes of secondary research.
Secondary Research: Secondary research is the most used and one of the efficient ways of data mining. Data mining is performed through various paid, non-paid, and in-house databases. Our paid databases include – Factiva, Hoovers, Zoominfo, Lead411, etc. Apart from the paid version, we also use our updated in-house database to pull out relevant entries. In the case of other non-paid sources, we only use government or industry association data, company annual report, investor presentation report, or such authentic sources.
Our Process:
Systematic discussion on Scope Identification
Development of Research Design
Client Approval on Database Structure
Changes or Modification if Required
Analysis and/or enrichment of data
Final Deliverables
Service Bucket:
Competitive Data Extraction
Social Data Extraction
Key Person Data Extraction
Production/ Service Data Extraction
Business Data Extraction
At Indlysis, We also offer web scraping services that simplifies the unstructured data into a meaningful structured database. After scrutinizing the formatted data, it then converts into a presentable format for final delivery.