Ensure your organization’s data is secure, high quality, and easily accessible. We can help with planning, rationalizing, building, and protecting data repositories including SharePoint, SQL, MongoDB, and connecting to other data sources. Additionally, protect what is important with backup to ensure a rapid recovery in the event of a disaster.
Aspects of Data Quality
Validity: The degree to which the data measure what they are intended to measure.
Reliability: Data is collected consistently; definitions and methodologies are the same when doing repeated measurements over time.
Completeness: Data is complete with no missing data or data elements.
Precision: Data has sufficient detail.
Integrity: Data is protected from deliberate bias or manipulation.
Availability: Data is accessible so it can be validated and used for other purposes.
Timeliness: Data is up-to-date and available on time.
Why is Data Management Important
Productivity: Quality data is essential for productive operations.
- Easier for your employees to find and understand the information that they need to do their job.
- Staff can validate results or conclusions they may have.
Cost Savings: Save cost through increased productivity and generate insights for further savings.
- Avoid unnecessary duplication.
- Save time ensuring data is easily referable.
- Data insights drive organizational innovation.
Operational Agility: Agility is a key factor in determining the long term success of an organization.
- If a company takes too long to react to the market or its competitors it can spell disaster for the company.
- Provides the structure for information to be easily shared with others.
- Allows information to be stored for future reference and easy retrieval.
Reduction in Security Liabilities: There are multiple risks if your data is not managed properly and your information falls into the hands of the wrong people.
- Greatly reduce the risk of losing vital information ensuring that employees know and follow proper data management practices as people are often the weakest link.
- Ensure that important information is backed up and retrievable from a secondary source if the primary source is ever inaccessible.
Better Business Decisions: Business information is critical for planning, trends analysis, and managing performance.
- Within an organization, different employees may even use different sources of information to perform the same task if there is no data management process and they are unaware of the correct information source to use.
- The value of information is only as good as the information source.
- Data entry errors, ineffective decisions, and processing inefficiencies are all risks for companies that lack a strong data management system.
Important Data Management Considerations
Consistent Data Collection and Recording: Develop processes to ensure data are collected consistently across different sites and different data collectors.
Data Backup: Have a plan for onsite and offsite, automatic, and manual processes to guard against the risk of data being lost or corrupted.
Data Cleaning: Place focus on detecting, removing, correcting errors and inconsistencies in a data set or database due to the corruption or inaccurate entry of the data.
Effective Data Transfer: Avoid the need to rekey data, have a strategy in place to move data between systems, including between software systems.
Secure Data Storage: Protect electronic and hard copy data in all forms from being accessed without authority or damaged.
Archive Data for Future Use: Invest in systems to archive data so that they can be accessed in the future.
MERAK Systems Corporation can help:
Automate: Replace repetitive tasks with intelligent automation.
Empower: Empowering our clients to develop and manage solutions for themselves ensuring they can remain technology relevant.
Manage at Scale: MERAK Systems Corporation provides the best practices to help manage and govern your organization’s creations at scale.
Visualize: Unleash a data driven culture within your organization through rapid reporting and analytics against business data.