How to work with Data Team?

I had a lengthy discussion with a "Data strategist".

I was curious to know what should we take care of when considering data strategists role and data.

If I have to help here, what are the elements I need to know?

With high-quality data, businesses are able to gain insights for stronger business decisions and strengthen efficiency and productivity. So Data is next Oil, no confusion about this.

But we need to overcome many challenges to reach their goal of gaining the drop in oil.

As a “ways of working”, team members, we need to facilitate the team to surmount all these challenges by hooking up the right dots.

What kind of mechanism we have to look at for Data collection, one of the important steps to master in Data evalutation process

• Interviews
• Questionnaires and surveys
• Observations
• Documents and records
• Focus groups
• Oral stories and records
• Financial Reports
• Sales Records
• Retailer/Distributor/Deal Feedback
• Client Personal Information (e.g., name, address, age, contact information)
• Business Periodicals
• Government Records (e.g., poll, tax records, Social Security intelligence)
• Industry/Business Journals
• The internet

There are many challenges to identify and work with the data.....

Challenges with Data Collection:

• Data collection standards are not up to the level
• Complexity with the data collection
• Intelligence about the data collection
• Appropriate users are missing or are not able to feed the information

Challenges with Metadata:

• Missing Effective metadata technology
• Costly implementation
• Substandard technology selection
• Disparate information sources
• Authenticity and standard of the data

Challenges with Data Quality:

• Data Duplication
• Outdated data
• Hidden data
• Ambiguous data
• Inconsistent data
• Too much or too fewer data
• Data changes too fast

Challenges with Data Governance:

• Data are siloed
• Data are not controlled
• Poor leadership
• Data quality
• Poor data Documentation
• Data Ownership
• Organization structure
• Data Opacity

Data Security Challenges:

• Find what data needs to protect
• Remote work
• Deal with multiple security solution
• Deal with Physical security
• Insufficient security configuration
• Fake data
• Data Manipulation and wrong data injection

Data Design Challenges:

• Design standards
• Data Processing speed
• Focusing end-to-end data requirements
• Poor documentation

Data Architecture Challenges:

• Evolution of methodologies & culture
• Adapting to changing architecture
• Complex data environments
• Data quality
• Business focus
• Dealing with Large Volumes of data
• Data Integration
• Data technology selection
• Scaling data

Data Science Challenges:

• Find the right data
• Data cleaning
• Understanding business problem
• Collaboration with diverse stakeholders
• Understanding KPI & Metrics
• Imbalance data

Have you worked with Data Strategist? What are their key traits?

Data Strategist need to work with all the teams to overcome all these challenges.

Share your thoughts when you work with Data/Analytics team, what else they are doing to overcome those challenges?

DATA PYRAMID!

My friend, who is selling online cake, she is again considering data strategist to magnify her sales

I have picked up a lot from her cake business, she recognize the power of data and regular basis, she collects, stores, analysize those data for meaningful outcomes

• She compiles information to take decision
• She discovers insights and strengthens knowledge from that data
• She tracks business performance and progress
• She generates early warnings about her business
• She deals with vendors, suppliers with this data for better collaboration
• She shares the data report to all the individuals who are partnering with her
• She optimizes flow wherever required

It has turned into unquestionably a competitive advantage for her to sell the cake at the optimum price and optimum time by using the Data power!!

Her Cake service quality has risen after all these steps.

I am certain our stock market investors are considerably better in this skill and they have magnified the power of data for the decision making. Some are successfull some are still analyzing why I made this investment as Data is not everything!!