Data Maturity Assessment

Data Availability

Data Accessibility

Data Consumability

Data Actionability

1. Which of the following best characterizes your enterprise level data strategy?

On-premises

Multi-cloud – Distributed/federated

Hybrid cloud strategy – On-premises and cloud but distributed

Primary cloud strategy with a focus on multiple consumptions capabilities

Data Availability

Data Accessibility

Data Consumability

Data Actionability

2. How would you define your overall data integration maturity?

Manual framework for data intake and processing

Disparate ETL tools along with manual transformation processes

Multiple tools with a common framework for data delivery

A single enterprise-standard data integration platform

Data Availability

Data Accessibility

Data Consumability

Data Actionability

3. How will you rate compliance and data privacy in your organization?

There is no sensitive data

Only customer data is considered sensitive, and the rest follows standard data privacy policies

Dictated by information security and company policies

Strict adherence to regulations and compliance

Data Availability

Data Accessibility

Data Consumability

Data Actionability

4. How is data being stored within your organization?

Data is not saved in an organized or standardized manner

Data is mainly kept in spreadsheets on local computers or in siloed databases across the organization

Data is stored in a central data warehouse

Data is stored in a data lake, where it can be utilized extensively across the organization

Data Availability

Data Accessibility

Data Consumability

Data Actionability

5. Is there rejection of data requests from business users due to the non-availability of data? If yes, what percentage?

More than 50%

20 to 50%

10 to 20%

Less than 10%

Data Availability

Data Accessibility

Data Consumability

Data Actionability

6. How would you describe the stability of your organization’s data landscape?

Too many changes in the last one year

Significant changes before the last six months but few changes now

Few changes in the past six months but many before that

The landscape is stable and has not undergone significant changes recently

Data Availability

Data Accessibility

Data Consumability

Data Actionability

7. Does your enterprise landscape include structured, unstructured, and third-party data? If yes, how much of these data sets are available for real-time consumption?

No unstructured or third-party data involved

Yes, periodic data availability based on requests

Yes, near real-time availability of data sets

Yes, all data sets are available in real-time

Data Availability

Data Accessibility

Data Consumability

Data Actionability

8. How is the data accessed for business consumption across your enterprise?

Each line of business owns its own data, but it’s completely ungoverned

Managed manually with a higher lead time

Federated, but completely automated

A single version of truth for all businesses

Data Availability

Data Accessibility

Data Consumability

Data Actionability

9. How would you characterize real-time reporting capabilities in your organization?

I never get the information when I need it most

There is a process of getting urgent information, but it is too cumbersome and bureaucratic

The infrastructure enables me to get it, but it’s quite complex and requires technical knowledge

We have a fully integrated cloud platform for on-demand reporting needs

Data Availability

Data Accessibility

Data Consumability

Data Actionability

10. How much of the enterprise data is considered redundant or devoid of any usage?

More than 40% of the information

15 to 40% of the information

5 to 15% of the information

Less than 5% of the information

Data Availability

Data Accessibility

Data Consumability

Data Actionability

11. How do you describe the business perception of data usage/consumption in your organization?

Poor perception with no usage of data for meaningful decisions

Average perception with limited use of data for daily business needs

Mixed notion where data is validated before taking decisions through data quality checks

Perceived highly with all decisions based on information available in data lakes/data warehouses

Data Availability

Data Accessibility

Data Consumability

Data Actionability

12. Access to right information in the right form and at the right time is critical for enterprises to make intelligent business decisions. Which of the below options most accurately describes this process in your organization?

Users create their own set of applications with data directly extracted from the source

There are too many systems, and it adds to the confusion; there is no endorsed set of metrics

The IT team acquires information and subsequently shares it with the business stakeholders

Self-service approach – the right information is made available to all stakeholders in real-time

Data Availability

Data Accessibility

Data Consumability

Data Actionability

13. How do you capture the information needs of business units in your organization?

The data operations team reviews reporting needs based on ad hoc requests from application users, and key business stakeholders validate it

Each business unit defines its needs at the beginning of the year

Design thinking workshops conducted with key business personas

Periodic digital assessments

Data Availability

Data Accessibility

Data Consumability

Data Actionability

14. How will you characterize your analytical capabilities in the current technology landscape?

Non-existent analytical capabilities

Access to standard reports but limited analytical capabilities

Reporting and analytical capabilities of specific user profiles

Full-fledged reporting and analytical capabilities

Data Availability

Data Accessibility

Data Consumability

Data Actionability

15. Are reports automated within your organization?

No automation is in place; we manage all reporting tasks manually

We sporadically use automation using legacy tools, such as Excel and VBA

We have automated core reports using BI platforms

We automate all reports using a combination of AI and ML

Data Availability

Data Accessibility

Data Consumability

Data Actionability

16. How would you describe your data quality protocols for the cloud/big data platform environment?

There is no enterprise-wide data quality strategy

Data quality is not an explicit focus area but whenever a data error is reported, we investigate the issue

Data quality monitoring happens as data moves to data lakes/data warehouses

Data quality monitoring happens at the source itself

Data Availability

Data Accessibility

Data Consumability

Data Actionability

17. How frequently is the metadata managed and updated in your organization?

We do not maintain metadata regularly

Updates are periodic as stated by the CDO or the data office

Updates are event-/need-based

We update it in real-time

Data Availability

Data Accessibility

Data Consumability

Data Actionability

18. What kind of data governance model exists in your organization?

We do not follow any data governance model

Limited data governance capabilities with focus only on data privacy

A dedicated data governance body owns all critical data elements

Lean and automated data governance aligned to industry standards

Data Availability

Data Accessibility

Data Consumability

Data Actionability

19. How would you rate the integrity of the data consumed by business users in your organization?

Less than 75%

75% to 90%

90 to 95%

More than 95%

Data Availability

Data Accessibility

Data Consumability

Data Actionability

20. Do you have standards in place that drive best practices for generating business insights?

There are no agreed or published standards

Documentation exists around analytical processes, and we recognize the need for standards

Guidelines are documented thoroughly, and we have enforced standards across the organization

Advanced processes involving extensive use of AI are in place to enforce best practices for insights

Slacking:

Your business currently lacks the capacity to fend off the disruptive elements of data. Act fast to seize advantages that can help you move on to the next stage.

Investing

Cruising

Trailblazing

Slacking

Investing:

You are moving in the right direction, albeit at a slow pace. Consider alternatives to expedite the data maturity process to enjoy a greater market advantage.

Cruising

Trailblazing

Slacking

Investing

Cruising:

You’ve outpaced the laggards in your industry and are on higher ground. However, this is merely a temporary solution and requires more work to reap the benefits of your data and analytics programs.

Trailblazing

Slacking

Investing

Cruising

Trailblazing:

You are one of the few in the industry who’s setting the bar for combating disruptive forces. Your existing data landscape needs to be iterated upon to ensure sustained improvement across all fronts.

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Data Maturity Assessment

Data Maturity Survey Questionnaire

Score For Data Maturity Assessment

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1. Which of the following best characterizes your enterprise level data strategy?

2. How would you define your overall data integration maturity?

3. How will you rate compliance and data privacy in your organization?

4. How is data being stored within your organization?

5. Is there rejection of data requests from business users due to the non-availability of data? If yes, what percentage?

6. How would you describe the stability of your organization’s data landscape?

7. Does your enterprise landscape include structured, unstructured, and third-party data? If yes, how much of these data sets are available for real-time consumption?

8. How is the data accessed for business consumption across your enterprise?

9. How would you characterize real-time reporting capabilities in your organization?

10. How much of the enterprise data is considered redundant or devoid of any usage?

11. How do you describe the business perception of data usage/consumption in your organization?

12. Access to right information in the right form and at the right time is critical for enterprises to make intelligent business decisions. Which of the below options most accurately describes this process in your organization?

13. How do you capture the information needs of business units in your organization?

14. How will you characterize your analytical capabilities in the current technology landscape?

15. Are reports automated within your organization?

16. How would you describe your data quality protocols for the cloud/big data platform environment?

17. How frequently is the metadata managed and updated in your organization?

18. What kind of data governance model exists in your organization?

19. How would you rate the integrity of the data consumed by business users in your organization?

20. Do you have standards in place that drive best practices for generating business insights?

Slacking:

Investing

Cruising

Trailblazing

Slacking

Investing:

Cruising

Trailblazing

Slacking

Investing

Cruising:

Trailblazing

Slacking

Investing

Cruising

Trailblazing:

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