If your eCommerce, ERP, CRM and marketing tools don't share the same “truth”, you're going to feel it everywhere: reports that don't close, duplicate customers, outdated inventories, and teams discussing which system is “right”.
When data is spread over so many spaces, it is normal for silos, inconsistencies and repeated records to appear. La data integration, exists precisely to avoid such chaos, by combine and harmonize data from multiple sources in a consistent and usable format.
Google Cloud He sums it up like this: data integration is bringing together data from different sources to obtain a unified and more valuable view, allowing us to decide better and faster.
In practice, this usually attacks very specific problems:
In data environments (and especially customer data), Bounteous warns that without unification, information remains fragmented, making it difficult to extract insights and deliver personalized experiences.
Microsoft Azure, meanwhile, defines data integration Like the process for combine data from multiple sources and give users/areas a unified view.
In practice, Integrating data involves identify sources, extract, map, validate/quality, transform (cleaning/standardization), load and synchronize, in addition to governance/security.
La data unification focuses on build a unique and reliable view from different sources and different attributes. And, key to your title: include identify and merge duplicates (for example, “Juan Pérez” in CRM, “J. Perez” in eCommerce, “JPérez” in support).
Reltio describes it as a broader process: cleaning/normalizing, creating unique identifiers, detect and merge duplicates in trusted entities. In addition, it warns that when data is spread across platforms, inconsistencies, errors and duplication increase.
There are three typical causes:
The realistic goal isn't “zero copies” in any scenario; it's avoid unnecessary duplication and, when there are copies per performance/operation, that they are controlled and consistent.
There are several typical integration methods: ETL, ELT, data virtualization, CDC, integration via APIs.
As strategies, we can also mention the replication, virtualization, change data capture, streaming, in addition to ETL/ELT.
Rivery It also defines ETL and ELT, noting that in ELT the transformation occurs subsequently of loading raw data to the destination.
Would you like to take the first step in your business?
If your priority is avoid duplication by design, there are two concepts that appear strongly in the sources:
In simple terms: if you don't need to persist everything in a central repository, virtualization/federation may be the most direct path to unifying “without cloning”.
Google Cloud describes CDC how to capture changes at the source and replicate them to the destination in real or near real time. IBM also mentions CDC as a form of real-time integration, applying source updates to data warehouses or other repositories
According to IBM: create a virtual layer to query integrated data “on demand”, without physical movement. Microsoft Azure Also ready Data Virtualization as an integration strategy.
When is it good for: operational reports, need for agility, access in near real time.
In the federation, the data they remain in their systems and queries are cross-executed in real time; it reduces duplication, but it can have performance challenges.
When is it good for: when you don't want (or can't) centralize; analysis with scattered sources.
Essential part is Resolve duplicates and merging them into trusted entities; and its “step by step” includes cleaning/standardization and merging redundant entries.
When is it good for: single customer, single product, single supplier; avoid “three versions of it”.
Aim at virtualization or Federation to achieve a unified view without replication.
If you need to consolidate into a destination (warehouse/lake), “non-duplication” becomes a problem of quality and resolution of entities. Reltio describes that unification includes create unique identifiers and merge duplicates in trusted entities.
Bounteous states that without unification, customer data is fragmented and it becomes difficult to extract insights and personalize experiences; this is why it mentions the use of tools such as CDPs, MDM and CRMs as part of the unification ecosystem.
Would you like to take the first step in your business?
This is where theory becomes operation.
With the Weavee Universal Connection, a Central hub to connect systems (ERP, CRM, eCommerce, etc.) and centralize information eliminating manual processes. It also includes real-time monitoring, with alerts to keep the operation under control.
What do you gain from this, in business language?
Integrating data is combining and harmonizing sources for operational/analytical use. Unifying data adds a critical layer: resolve duplicates and build trustworthy entities.
If you want it to really work, define your unified view, establish quality/redupe rules and choose the strategy (virtualization, federation, ETL/ELT/CDC) as appropriate.
Ask for a test and we put together an integration/unification plan aligned with your operation.