It is so clear that for any effective public service delivery, resource allocation that is efficient and for any policy-making that is meaningful, a very high-quality data development is a necessity. As much as the introduction of new technologies has been widening the uses of data and making more data possible, there still exists a gap in the global data map. Research has shown that a few years ago, more than 70 countries were lacking the data needed in adequately measuring poverty.
Often, our biggest disappointment has always been data has always been scarce in areas that it is needed desperately. Despite the need to urgently manage the increasing climate changes and the making of the decision to aid in reducing the disparity of gender, there still remains a significant void in data development. There are so many other areas such as infrastructure, food security, education and health where data development is essential to deliver progress.
What is data development?
Data development is the implementation, analysis, deployment, design and maintaining of data solution as a way of maximizing the data resource value to an enterprise. This involves the generation of solutions that are technology-driven so as to enable data to be moved from one place to another. This could involve moving things from a data reporting system to a data generation system or vice versa or the various development task system that enable many other data management association domain(DAMA) to correctly function. But what exactly can be done in improving data development? There 3 things that need to be done as shown below.
Focusing on the frontier and the fundamentals
Civic registration, household surveys and administrative data are the building blocks of data development that are critical components in working to better the lives of people worldwide. New sources and new technologies such as satellite imagery and geospatial data have always offered a large amount of data that never existed before and that will aid us enhancing precision, increasing accuracy and managing and understanding our world better. This may need us to push the frontier by growing our own expertise in the various new types of data and also in learning machines to skill up our data analytics.
Balancing data protection and data profusion
The data world is changing but being in a world where data profusion is always parallel to data governance and this includes proper personal data protection, curbing the misuse of data is very essential. This will help in ensuring that data is serving a social purpose that is higher. What the world is urgently seeking is data governance that is based on values that are recognized universally and where tech experts and legal experts are brought together. Also, when dealing with data, statistical tables should not be the end and it is good to ensure that data is improving the lives of people. In order to get there, there is a need to support the literacy of data and investment in the capacity of people in changing data into policy outcomes that tend to affect the lives of people in ways that seem to matter most.
Investing in ideas, data and people
Finally, putting our priorities into practice involves committing ourselves to comprehensive financing of data development. This includes investing in every step of the way from improving the methods of collection, curation and anonymizing of information and also growing their ability to analyses and use data. Data scientist and statistical also need to be supported in ways that will help them move forward by encouraging the integration of new and creative data uses. Also in the creation of global public goods, there is a need in investing in ideas that are innovative through pioneering new ways of applications of data technologies.
Available work positions
There are various positions that need to be filled for a successful data development as data is changing and regardless of the industry in which is operated, data jobs seem to be exploding and there are various positions available with attractive salaries.
- Data security administrator with a salary of $79000 annually.
- Data analytic manager with a salary of $50000-110000 annually.
- Data engineer with an annual salary of $80000
- Database administrator with an annual salary of $80000.
- Database developer with an annual salary of $90000.
- Business intelligence analysts with a salary of $70000-90000 annually.
- Data scientist with a salary of $ 100000 annually.
The general requirement for the above jobs are as follows
- Problem solving that is data-driven
- Efficient and fluent communication.
- Short courses and featured certificates in data development
- Be familiar with software/programming
- Statistics sensibility
- Be able to present data in a visually compelling way.
With the increasing global issues, we need to come up with new ways of approaching and solving issues and one of the best ways is through data development. With the increasing changing technologies data development has become the easiest and the most efficient way of coming up with solutions to almost every problem.