Top 11 Data Governance Software Solutions

We live in a highly digital and information age. We tend to disregard this as everything seems to be right there at a flick of our hand or just one click of the mouse. But we warned. All the more, there is a big need to scrutinize and determine the veracity of the information we are getting.

There is now a new emerging framework wherein data management, quality and processes involved is deeply entrenched in a sustainable and holistic management wherein risk in decision making for data are considered. It means that from sources, storage, modeling and analysis up to dissimnation, there are control points for the organisation to follow.

Data governance involves putting up of quality control points in each step of the data mining and warehousing. The data used int he organization should be handled well and there are rule book as to who is responsible. For instance, there are data stewards for hard copy of files but most of the time, digital files are left to the Information Technology personnel. But this should not eb the case. In the spirit of uniformity and also easy access and storage, there should be a form of uniformity like say, in the file naming of the data, in the choice of sources and the length of time these data ae to be kept.

Will this be kept in an internal server or an external free one like a Cloud will be used? What level of confidentiality will be open to rank and file staff? What is for the internal usage versus for all of the customers?

The data governance spells out who is responsible for what and also shows the processes to ensure quality of the data. It shows the processes taken by the company to become it more efficient. It is a discipline wherein control and processes are also done by every staff. everyone understands the process in handling the information, whether this is sensitive or for general use.

Information are empowering and when properly used, this will benefit not just the individual but foremost the organization. It is a quality control for managing, improvising, maintaining and foremost, protecting the sensitive organisational data. The decision rights and who is accountable in every step. This should be discussed earlier on so as to avoid the risk.

Decision rights and responsibility framework are outlined and this is one indicator of the maturity of one organization. This is crucial especially when data marts and data subsets will also take on copying of information from the centralized data warehouse thus there should be a standard to follow. This is to ensure effective and efficient data use and for the information to be used by the proper personnel for decision making and for organizational marketing, to ensure better sales.

Take in mind that it it will not solve every problem in your organization but the data governance will ensure and define finer points for strategies in the storage and delivery of data. Procedures, monitoring and also evaluation are entrenched in the process. Take note that data should be optimized and cost effective.

The Data Management Association (DAMA), a non-profit international association advocates for the information resource and risk management. According ot its study, the following are one the recorded best practices for data governance:

1. Think long term but start small.

A holistic approach is needed but do not take too fast. You have to contend with organizational culture and politics and you are dealing with people. Change takes times and there should be gradual steps to take. Balance your end goal with the carrying capacity of the organization and the staff involved.

2. Take some sponsorship (if you must).

Changes especially for data management will require money. Technology requires cost so you have to balance the free meals (free softwares available!) and those that will need longterm capacity. This is a fundamental organizational change and it would require leveling off of the people.

3. Outline who got the control and stewardship of the data.

The early stage is crucial and key responsibility and accountability should be outlined. Who is responsible with what and this should be properly documented. So take a look-out of the stewards and should not only the IT person but those with the keen eyes for details. This should be also outlined in the job description of each employee.

4. Put indicators to measure progress and success of the plan.

At the onset, monitoring and evaluation is part and parcel of the governance management. For the division, check out the data subset in the division and see how the clear outline of the data helped them. You can choose to take the quantitative and also take on the qualitative aspect by asking them to be part of the process.

5. Give incentives to ensure participation.

You know reinforce positive attitude? By having clear indicators for progress and monitoring, then reinforce this by allocating the resources. Try it at department/ division level at first to take on commitment from every staff.

The key to sustainable data governance is ensuring that everyone understands the overall goal for data and risk management.

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