Salesforce Data Management
Explore the powerhouse of a managed data with Serigor
Salesforce is all about data, but a lot of companies struggle with proper data management. Handling acquired data and making data-driven decisions play a key role in getting the best out of Salesforce when customer satisfaction, higher sales and marketing are your vision.

Data-driven sales and marketing solutions is the new black, so it is believed in the tech world. The digital transformation itself is powered by data and the structural path laid by it.
How an IT operations, infrastructure and maintenance partner can help you?
Data Cleansing – Data Cleansing is probably one of the most important aspects of data maintenance. Handling a huge influx of incoming data, and putting them in silos to offer easy monitoring, usage as well as cleanup of invalid data, is where Serigor helps you and your team. We ensure you do not struggle with outdated, wrong, misleading, missing and duplicated data.
Data Integration and Migration – Data Integration and migration need the most expert hands on deck. The nature of data and the challenges involved in its secure migration can be overwhelming. Serigor’s data architects are well aware of all potholes and solutions there are to deliver the most effortless data integration and migration while your team continues working with the data in hand.
Data Security – Data Security cannot be taken lightly especially when an organization’s customer dealing and internal structure sits on top of it. Data management is also data monitoring. We monitor the efficiency, quality and threat surrounding your data to ensure there is no corruption, deletion and poaching.
Data Defining – Source of truth or data defining helps you understand the performance of your salesforce data. A dynamic dashboard from Serigor will help you know your data, its quality, accuracy, fitness, its effect and how every other information you need on your salesforce data.
How does Serigor’s Data management consultation work?
Often the most basic errors made when managing data are about:
Cleaning up of acquired data
Handling outdated or duplicate data
Controlling the data flow
Data integration and Migration
Streamlining the overload of incoming data
