At a time when an enormous amount of data is being captured from numerous sources, unlocking its value offers humungous opportunities for businesses to harness its potential and derive intelligent insights.

 

It has been proven time and again that without a robust approach to data collection, data mining, data cleansing, data processing and data security even the best of Digital technologies will not help in successfully harnessing the data and generate value for a business and its customers.It is therefore key that organizations align strategic, organizational, and technological choices with the overarching goal of leveraging data as a strategic asset.

 

1. Data Silos

 

Data is generated from different sources in different formats with varying parameters and inconsistent interpretation. This leads to data silos and data silos increase the difficulty of ensuring data quality. 

 

2. Lack Of Centralization

 

Fragmented data makes it difficult to achieve a high-level, enterprise-wide view of what is happening in the business.Without a holistic view of the performance of the business it will be challenging for leaders to take critical business decisions.As a result, leaders could miss out on opportunities to implement proactive strategies that can increase operational efficiency, reduce errors, improve quality, and generate more value from data.

 

3. Poor Security 

 

Data fragmentation makes it nearly impossible to collect the right data and weaken the ability of the organization to put in place the security protocols necessary to protect that data from unauthorized access. Without security measures and data access control, organizations open themselves up to data breaches and loss of IP.

 

Key Components of a Data Strategy

 

Typically, the key components of a data strategy are:

 

• Alignment with corporate strategy

• Data architecture 

• Data governance

• Cultural change management

 

a. Alignment with Corporate Strategy

 

It is important to recognize what data is relevant for the business and how that data will be used to achieve business goals. You need to map your data strategy with the business strategy which will form the basis for all the other steps that follow.This underlines the need for clear and transparent communication between business and IT about the metrics that will be required to be applied and tracked, the key stakeholders and the roles of these stakeholders. Continuous monitoring and feedback loops will also go a long way in ensuring there is strong alignment.

 

b. Data Architecture

 

Data architecture and technology are essential to asuccessful data strategy;without the right tools and architecture, organizations struggle to effectively capture, store, analyze and use data. This can lead to an ineffective data strategy that does not add value to the business. Data architecture determines how data is stored, accessed and used within the organization. 

 

c. Data Governance

 

It involves establishing policies, procedures, and standards that support the collection, processing, and use of data within an organization. Effective data governance ensures that business data is handled securely and responsibly, while enabling its use in line with the organization’s business objectives.Data governance can be divided into two main components: Data Management and Data Security. 

 

C1. Data Management

 

This is the process of collecting, managing, storing, retrieving, and integrating the data. 

 

The benefits of good data management include increasing the impact of research, adding fuel to innovation and experimentation, ensuring data integrity and data validation, avoiding duplication of effort and maximizing value.

 

C2. Data security

 

Data security is about establishing a permission framework that prohibits certain users from accessing certain data sets or performing various operations.Effective security measures are critical to prevent unauthorized access or data misuse. This can include technologies such as multi-factor authentication or encryption techniques.

 

d. Culture change management

 

Above and beyond, fostering a data-centric culture in a company is an essential prerequisite for a successful data strategy. This starts with the example set by top management as well as executives. This requires not only technical skills, but also that employees are properly trained, empowered, and supported. And finally, communicating the success achieved with data assets is crucial when it comes to increasing employee engagement. 

 

In summary, a successful data strategy should have an over-arching plan that could support business strategy to enable a long-term foundation for future business strategies and growth.