Evolution of the search algorithm for a proprietary insights platform
DigitalMara strengthened the client’s data engineering team to help with optimizing and refining search functionality within an insights platform, which provides insights on leadership and executive search.
About the client
DRAX Executive
DRAX Executive is a UK-based consulting firm that conducts assessments of companies and their leadership to identify and highlight potential drivers for success. It also aids in the search for new leaders who will perfectly fit the given company's needs, based on their experience and achievements. DRAX’s work is supported by its proprietary insights platform, which offers a unique analysis algorithm. The platform can be used both by DRAX for consulting and by the company’s clients individually.
Challenge
The client came to DigitalMara with the need to scale their data engineering team to accelerate development. They already had a simple ETL (extract, transform, load) platform with some front-end parts and wanted to extend its capabilities, to improve search accuracy and speed. As one of the main processes in data warehouse management, ETL must be able to efficiently handle raw data from external resources, extract the relevant data then clean and transform it into the form needed for subsequent use.
Data needed for analysis is collected from various sources. The main problem with this type of information is the wide variety in format, syntax, and content. For example, work responsibilities and positions of candidates can be described in numerous ways: a similar role may be titled chief marketing officer or director of marketing, trend analysis or market research. For proper matchmaking, it is necessary to consider these discrepancies. In addition, fragmented data needs to be classified, organized, and correctly interpreted for visualization to users.
Approach
DigitalMara has been involved in improving the search and data processing components within the DRAX platform, particularly in the improvement of the Search API (Application Programming Interface). This API is connected to the ETL and makes it possible to conduct accurate and detailed full-text search in large data volumes and, even more importantly, to create indexes that lead to more convenient and faster search results for the system’s users. If the data received is incomplete, incorrect, or distorted, additional processing is performed to clean up the data and bring it into its proper form, while unverifiable data is deleted.
Results
Implementation of smart search made it possible to increase system productivity and the quality of search and processing. In particular, the speed of search and index creation has increased by four to five times. This has resulted in delivery of a better user experience within the platform and efficiency through using it.
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