Automated Data Discovery
Strengthen your business intelligence through smarter data management.
Find the data you need anywhere in your data landscape, in seconds.
Automated data discovery enables instantaneous search and location of your desired data across multiple systems.
Let’s do things smarter…
Gain insight into all the SaaS applications in use within your organization, including unknown applications along with previously known and sanctioned applications.
Data Discovery is the first step to knowing your data. Auto-discover data across any application on any infrastructure and identify all unknown data relationships across the entire siloed data landscape.
Quickly search, explore and understand critical patterns and relationships in your data, then visualize complex dependencies between data attributes, and represent relationships between entities. Automatically identify sensitive data and tag it for classification in order to ensure compliance.
Discovery & Automation
Data teams can easily leverage their data without a dedicated support team. Automation and workflow orchestration for your data tooling removes siloes between stages of the data pipeline, making it easier to understand and access data. Greater accessibility naturally leads to increased data adoption, reducing the load for your data engineering team.
Scalability as Data Evolves
As you ingest more data and unstructured data becomes the norm, the ability to scale to meet these demands will be critical for the success of your data initiatives. Data discovery leverages machine learning to gain a bird’s eye view of your data assets as they scale, ensuring that your understanding evolves along with your data. This way, data consumers are set up to make more intelligent and informed decisions instead of relying on outdated information and processes.
Data Reliability, Today & Tomorrow
Modern data teams have automated approaches to ensuring highly trustworthy data at every stage of the pipeline. The Kleene ELT Platform provides everything from data quality monitoring to end-to-end data observability, and can alert for issues in your data pipelines. Quickly finding the root cause for fast resolution and preventing future downtime.
The Kleene Data discovery empowers data teams to trust that their assumptions about data match reality, enabling dynamic discovery and a high degree of reliability across your data infrastructure, regardless of domain.
Read Our Success Stories!
Home » Case Studies » HuelCase Study: Huel58 FTE days per month saved Reconciliation down from 3 staff x 2 weeks to under 2 days for a single user> £100k per annum saved In engineering resource, reconciliation effort and management time.Rapid data pipelines...
Home » Case Studies » LakaCase Study: Laka6 FTE days/week saved50% of all reporting requests available from self-serve.> £70k per annum savedin data engineering resource and management time.Curated Self-ServeBusiness stakeholders able to make informed...
Home » Case Studies » Blue Light CardCase Study: Blue Light CardRenewals target increase from -14% to +7% of target.77 cross-function reports built across 12 themes.50% of the business now uses Tableau.About Providing a discount service to emergency service...
Connect your most important platforms in minutes
Out-of-the-box integrations unlock the value trapped within existing systems. Spare your engineering team from another tedious implementation and connect data instantly.
Our Latest Blog Posts
A strong and dynamic market requires businesses to adapt quickly to remain competitive in their industry. Data has become the most fundamental asset, but how can you accelerate your data transformation to extract value from your data?
Data is transforming the way businesses operate, and data volumes are growing. The challenge is, how do we use this data to create insights that can formulate and direct our business strategy for competitive advantage?
At Kleene we see a lot of companies using a transactional database for reporting purposes. This can work for some companies, for a certain amount of time, but in reality, it just isn’t scalable.
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