December 15, 2022
When it comes to data, there is one term that is as relevant today as it was 20 years ago: garbage in, garbage out. If your data is garbage or chaos, anything you attempt to do with it will, unfortunately, churn out more garbage. What is data chaos? We’re glad you asked. Data that is fragmented, trapped in silos, hidden in legacy systems (“dark data” is what we like to call them), incomplete, duplicated, or poorly identifiable are all indicators that your data is in chaos.
Data has a tremendous opportunity to change how we do business today. But there’s another side to it; there’s much responsibility with that opportunity.
Fragmented silos of business data are required to preserve the integrity of information while still enabling a streamlined approach to managing it. Data must be identifiable and indexable. Data quality and integrity must be ensured by matching records and eliminating duplicates. Metadata must be established to ensure consistency and integrity for effective search and management.
But the fact of the matter is as enterprises today constantly produce tremendous amounts of data, it also exponentially increases the complexity of data governance and data lifecycle management. However, due to fast-growing and unstructured data, it becomes very difficult for organizations to manage them. This increases data chaos inside organizations.
Having clean, structured, and complete data is now more important than ever. Why? Because data in chaos can hurt your company. Badly.
Most of the time, your data situation is in such chaos as a side effect of operating on legacy systems. But enterprises are very cautious and concerned about migrating away from legacy software, such as legacy enterprise content management (ECM) systems, because of how deeply ingrained their data is. It is a perfect illustration of a catch-22 scenario.
Opting to keep operating using legacy systems comes with exorbitant costs, complexity derailing organizational efficiency, and missed opportunities. Thanks to the legacy systems, new data your organization creates or produces is going straight into chaos. Soon, many of your new data will be trapped in siloes, become “dark data,” fragmented, and duplicated. This can impair the speed and efficiency of your enterprise.
Whether you choose cloud or on-prem, you need to start legacy modernization and migrate your systems--especially legacy ECMs--to more modern platforms. With the help of professional data and ECM migration partners like Helix International, you can choose different migration options and scenarios that best fit your enterprise.
General Data Protection Regulation (GDPR) from Europe and California’s Consumer Privacy Act (CCPA) are just two of the several data privacy laws companies must comply with regarding their collected data on consumers and users. The scope of both of these laws is wide, and the scope of organizations affected by them is vast.
Any company that doesn’t comply with these data privacy regulations faces steep penalties. One fine example is the “right to be forgotten,” which allows individuals to request a company to permanently delete their information. Privacy laws mandate that compliance is mandatory. Compliance violations can cost several thousand dollars for each instance. Companies like Amazon and Google have been fined close to $1 billion in total due to non-compliance.
The only way your enterprise can comply with the requests for the “right to be forgotten” is if you have systems in place that can search and index all data or content which contains personally identifiable information (PII). This is a real operational and technical challenge when your data is in chaos.
Our proprietary software platform, MARS, can collate and unearth any “dark data” and forgotten assets, link fragmented documents and contents scattered across disparate databases and programs, and automatically organize content with shared metadata. MARS has 45+ connectors to data sources and also reads pretty much all filetypes in existence. Even if your data is in fragmented silos, thanks to legacy ECM systems, you can still use MARS for end-to-end data retrieval and migration.
Entity resolution could be defined as “who is who and who is related to who” in data. Entity resolution rules are used by enterprise data management systems to identify persons, organizations, locations, activities, and other “things”. This means that you need to have single versions of entities in your system to have complete data insights. But when you have entities in systems that are not linked, it will distort your records, leading to poor data integrity and consistency.
As data grows increasingly both structured and unstructured in scale, and the fact that we have more data to return than at any other time in recent history, the need to be able to identify entities across the data becomes increasingly important. Many times, organizations create different records for the same entity at different locations with slight changes over time. These records and entities are spread across multiple databases and systems across the globe and are difficult to find.
Using our MARS software platform, connecting fragmented and siloed contents and data for entity resolution is no longer an impossible mission.
At Helix International, we utilize our custom proprietary software developed over decades of enterprise ECM projects and our deep product and service subject matter experience. Our software and managed services teams have assisted 200+ Fortune 500 enterprises in migrating, converting, and optimizing their on-premises and cloud ECM systems.
We have individually tailored content and business process solutions to support our customers enhance their business operations and to guarantee that critical data is well protected, stored, and accessed legally.
Uncover data and solutions you never knew existed in the market. Talk to a Helix Data Expert now to see how we can save you time, lower your costs, and reclaim your human capital.
Massive savings in storage and compute costs. Our 500+ enterprise customers often cut their cloud bill in half or shut down entire data centers after implementing our solutions
