Case Study

Intel’s Waste Elimination

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The background

Intel is a multinational technology and hardware enterprise, headquartered in the US, with a $200B market cap.

As an industry leader, Intel sees data emerging as a transformational force in this era where an explosion of devices permeates all interactions. Intel aims to unleash the potential of data to unlock value for people, businesses, and society on a global scale. 49% of the corporation’s revenue in 2021 came from the company’s data-centric businesses.

 

The business challenge in this context

Intel collects large volumes of data and queries across various manufacturing units.
There are multiple data and analytics units within the Advanced Analytics organization that curate, transform and analyze data. The major data store for manufacturing analytics is on-premise with dozens of databases.

The challenge for Intel was to map all the assets they had, the PII and utilization perspectives of the data assets were the most important in identifying them. Another challenge was to identify duplications of datasets, pipelines, terminology and metrics, as well as to align terminology across the units.

 

The business challenge in this context

illumex got access to millions of metadata points from the Intel Microsoft Datamart.
In a matter of hours, the engine did the following:

  • Mapped hundreds of business terms with dozens of attributes;
  • Visualized the connections between business terms, metrics and analytics;
  • Showed the data layer utilization: whether the database/table/column was used or not, frequency of use,
  • queries and users it was used by;
  • Showed the duplications in business terms and tables;

 

The outcome

Intel called the project “waste elimination”.
When data and analytics are curated, Data Managers get full observability of the data and analytics activity assets usage. The process of finding duplicates, and understanding the lineage of the duplicate assets and their business logic content is quick and simple.
Using the illumex platform allows Intel to decide whether to deprecate the unused duplicate tables and pipelines, especially the ones that bear liability, like PII. The platform also simplified the process of onboarding a new data source (database in this case), where the initial familiarity with the logic is low.

 

Shirly Baruch, Director of Product Data Analytics at Intel

“While running illumex on Intel IT infrastructure we found that the technology has the potential to revolutionize the way we work since it takes queries and data objects and maps them automatically. This way, you can get backward engineering from actual objects that are used in production into a documented environment. It can reduce the need to maintain design documents. This Technology has the potential to support a digital transformation and eliminate manual work.

Another key benefit is that the Illumex technology allows you to see if there are overlaps. For example, you can observe a scenario where two teams are querying the same data, calling an indicator the same, but eventually, their indicators are formulated differently. You will know that there is a risk for one version of the truth.

We gave illumex metadata of our product engineering data environment, thousands of different data objects, and hundreds of thousands of daily queries.

Within a few hours, we saw the end-to-end dependency graphs and insights on top of the metadata and queries. Other tools are siloed, they are disconnected from the production environment, and updated only manually on demand.”



 

 

 

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