Role Of Data Manager And Responsibilities

The Data Manager is the one who deals with data management in the company. This role is responsible for ensuring the efficient and effective operation and use of information. The Data Management professional ensures the effective integration of the data management process with other processes, to meet service level requirements. Ultimately, the Data Manager is accountable to the owner of the data process.

Data Manager: Knowledge And Functions

The profile of the Data Manager would correspond to that of an expert professional in a variety of disciplines related to data management , such as the following:

• Data integration
• Data governance
• Data modeling
• Master Data Management
• Business intelligence
• Data quality
• Data Conversion
• Data warehousing
• Data architecture

According to  DAMA , the organization dedicated to advancing data management concepts and practices through research, education, publications, standards promotion, and other activities that improve data management practice; There are ten functions associated with Data Management, which include a total of more than 100 different activities 

According to the statistics published on Glassdoor , the salary of a Data Manager would be between 40 and 50,000 usds per year . In the United States it is slightly higher, being around 60,000 dollars per year.

For a business, having a data scientist on the payroll is a significantly higher investment . In the United States, the median salary for a Data Scientist is set at $120,000 per year.

Data Manager Responsibilities

Although the salary received by a Data Scientist can double that received by a Data Manager, each usd invested in a professional of this type is justified , since whoever occupies this position in the company:

Manages the effective implementation of backup and restore procedures and work practices.

Communicates changes and enhancements related to backup and restore standards, procedures, and technology

Review backups and restore reports daily.

Ensures compliance with the data architecture and data management standards and procedures defined in the organization’s data management framework for the cloud environment as well as on-premises.

It monitors storage management information, standards, procedures, measures, tools and technology.

Determines what reports are produced and controls the reporting schedule on storage resource capacity and utilization, availability, performance, and growth trends.

Be aware of storage incidents.

It works closely with Service Level Management to ensure that data management services remain capable of meeting current and future requirements.

Estimate overall storage resources, in the cloud and on premise, and budget requirements for asset management.

More responsibilities

Attends appropriate management-level support and development reviews (including vendor meetings and development meetings).

Compare and analyze process measurements associated with data management and recommend improvement activities based on service deviation.

Consolidates and feeds measurements from the Configuration Management process for management reports.

Assumes the responsibilities of the process manager for the data management process.

The digital transformation and the journey to the cloud have driven the arrival of more technological profiles in the organization . The result is a profound change in the IT Department, where many companies already have a Big Data Analyst or a Data Engineer on staff. However, although they have in common their knowledge of HR, SQL, Java or Python, communication and leadership skills and business vision define the Data Manager.

Who Is The Data Scientist?

The data scientist is an expert in data science who has a combination of unique skills, which allow him problems through the development of algorithms. His creativity is combined with his mathematical, statistical and programming skills, which he puts at the service of the business to generate value.

While data scientists often bring different educational backgrounds and work experience, most must be experts in four key areas:

• Business domain.
• Statistics and probability.
• Computer science and software programming.
• Written and verbal communication.

The data scientist will work in collaboration with the big data analyst, the systems engineer and the Data Manager, as well as with those responsible for the business area.