- A
centralised database can be of tremendous use while consolidating and processing raw data - Such a database can help sellers draw expert insights and create targeted campaigns
- We explore the various ways through which centralised and
intelligent database management can streamline and support sales operations
The key to systematic data synthesis is generating data using standardised techniques and incorporating best practices to process vast volumes of industry-segmented data. Consolidating raw data from multiple sources to create a centralised database can provide a complete view of the data of an organisation, equipping leaders to generate critical insights instantly. Sellers, when armed with such knowledge, can draw targeted campaigns to maximise sales.
There are several ways a centralised database can streamline operations in comparison to a distributed database.
- Eliminating Redundancy: A centralised database can prevent unnecessary duplication of data and minimise the time taken to process large datasets. It also results in saving storage space.
- Data Integrity: Centralised control of data can empower administrators to define integrity constraints and ensure regulatory compliance of data.
- Security: The administrators can ensure that access to the database is through secure and approved channels, due to their absolute control over operational data. If access to sensitive data is attempted without prior approval, the administrators can define authorization checks for higher security.
- Data Consistency: Companies can drastically cut down on inconsistent data by removing redundancies through centralised database management.
- Enforcement of standards: With the centralization of data, administrators can establish and enforce the data standards, such as naming conventions, data quality standards, etc.
- Reduced application development and maintenance time: A consolidated repository can support several processes that are common to various applications, such as retrieving data stored in the database to gain insights. This facilitates faster development of applications.
- Portability: Such a database is easier to use when compared to dealing with multiple sources of data. Data is stored in one location and can be easily copied, reorganised, or ported to another location if need be. This method is cost-effective too as it minimises maintenance costs.
To ensure data enrichment of contact information, businesses need to set up multiple validation engines, both automated and manual, across the data management process. Thankfully, today’s data management landscape is built on the foundation of future-ready powerful AI/ML-led algorithms and digital automation technologies. These unique capabilities allow companies the ability to access and process abundant data.
Effective database management requires constant data maintenance, data validation, and data profiling to uncover the right opportunities, enable a full-funnel strategy, and expand business growth.
Customer data is a critical asset for revenue enablement campaigns. However, its maintenance is hardly done well at scale. Data maintenance helps ensure that your database is accurate and effective by removing duplicate, outdated, and invalid records. This way organisations can continuously monitor and refresh their database to ensure the inclusion of fast-changing data and efficiently approach the sales-ready leads.
Data can be sourced through various channels or stored across several repositories in an organisation. This makes it critical to clean the data before using, importing, or otherwise processing it. Data validation can hence lay the groundwork for successful sales campaigns by verifying the accuracy and quality of raw data.
Companies turn to data profiling to stay competitive in the market and leverage their data sets in the best possible manner. Data profiling essentially examines a dataset, using digital tools or business rules to gain insight into the quality of data. This includes reviewing the accessibility, accuracy, and completeness of data. Such a detailed analysis can help organisations to cull out data inconsistencies and sift the single source of truth or error-free prospect data, at a high level.
At a time when sellers are struggling to keep up with the constantly evolving buyer’s expectations, being systematic with data can be of tremendous help. Intelligent database management has the potential to unlock massive growth in revenue and is a great asset against your competitors.
Disclaimer: This article is authored by