Is Foundry a data platform?
How does Foundry streamline the data integration process?
Is Foundry a low/code no code platform?
How does Foundry integrate with platforms like Data Bricks?
Is Foundry recommended to companies with a modern data platform? What is ideal data environment in which Foundry is best suited?
How Foundry makes life of a data scientist easier:
Data ingestion capabilities, ontology, and combination of CRMs:
How Palantir compares to Snowflake & other individualistic tools:
Is Foundry a data platform?
Foundry is the interplay between 3 dynamics: also referred to as an OS.
The 3 dynamics Foundry interplays within includes:
- Data platform: includes security, health-checks, versioning of data, pipelines at scale.
- MLOPS lifecycle: ability to deploy ML at scale.
- Operational workflows & application building: build applications via low/no code & define the business processes for set matters.
Overall, this creates an OS: PLTR is the interplay between these 3 main dynamics.
– The idea of a central operating platform can be broken down further into 4 main areas more fluently:
1) Firstly, through Palantir software, one can “drag & drop” certain tools, features, & partnered applications onto the project. This can be done fluently, meaning that the tools, features & applications communicate & work in conjunction with each other. As well as Palantir having innate tools (data visualization, AI, ML, ontology) within their platform, one can also leverage these innate tools, & use them in conjunction with partnered features & tools in order to derive the most value. Example of PLTR partnership with Amazon AWS: “Rapidly prepare data with Foundry’s data connection, extract, transform, load, and data branching capabilities, and then drag & drop AWS tools on to the project to analyse data and develop models.”
2) Orchestrate & bind the IT landscape together. This means that, instead of replacing old data systems & tools within the organisation, through Palantir, organisations can intertwine their own bespoke data systems & tools, in conjunction with more modern tools & applications – & overall use these in communication with each other.
3) Network effects refers to the low code, no code environment of Palantir OS. This enables anyone & everyone in the organisation to use the platform, create new applications & features, regardless of technical ability. Changes can be shared across the organisation, revealing how the product becomes more useful as more people use it.
4) Contextual data. Data is transformed into people, places, & things – which makes the data come to life.
How does Foundry streamline the data integration process?
Palantir perspective was originally: “how do we make data integration smoother for people who are on the front-line doing mission critical operations.” This therefore led towards their product HyperAuto within the OS, and also to build everything that engineers wanted within the OS innately.
1st aspect:
Palantir automates the streamlining process through their product HyperAuto. To explain, HyperAuto refers to the automated and dynamic data pipeline generation processor in order to achieve tasks in hours, in comparison to months or years via conventional methods.
What is a data pipeline?
A data pipeline is the set of processes that converts raw data into actionable answers to business questions. Overall, a pipeline automates the flow of data from source to destination. HyperAuto is a product that majorly increases the ease associated with a data pipeline, and therefore creates efficiencies and time-to-value improvements.
Palantir can streamline raw-data through HyperAuto, and instead of the output being unusable and unreadable, the output is an ontology that can drive business workflows. Palantir are expanding this to all types of systems that people are working with in all types of domains.
2nd aspect:
Build everything engineers need within the OS innately:
Nobody wants to go to a different tool to do health checks – this is all within the innate Palantir system. Palantir can unlock collaboration through robust security frameworks. Palantir builds assumptions into platform to enable one to go fast, but to do so safely.
Palantir is focused on, “what gets us to value as fast as possible and gets us to meaningful outcomes as fast as possible.” This reveals Palantir’s proposition of time-to-value. In other words, efficiencies, productivity improvements and overall costs being saved for organisations using Palantir Foundry.
Is Foundry a low/code no code platform?
Within Palantir sphere of operational workflows and application building, Palantir enables low-code/ no-code tooling functionalities. This is not the only option for technologists. There are also no-code, low-code and pro-code options available for developers and operationalisation users. Therefore, depending on the scope and comfortability, one can use the different options and derive value within a meaningful manner.
Also one can connect tools that do not exist on the platform, via an API, to model data into the ontology, and therefore build something with your own framework.
Whilst Palantir does offer low-code, no-code tooling, it is just one option among many for building.
What is a low-code/no-code solution?
Low-code/no-code development platforms are types of visual software development environments that allow enterprise developers and non-technical developers to drag and drop application components, connect them together and applications.
This is beneficial because, regardless of whom is technical within an organisation, there is an ability for everyone to derive utility from creation of these platforms. Overall, this can generate mass network effects across an organisation.
How does Foundry integrate with platforms like Data Bricks?
Palantir knows that most of the customers they work with already use many different technologies and tools. Therefore, Palantir has designed interoperability and has a commitment to open standards across set layers.
If one is doing some of the data transformation work in Data Bricks, or another platform, there are options to integrate this fluently within Foundry. This can help individuals get to value faster because interoperability is built from inception.
Is Foundry recommended to companies with a modern data platform? What is ideal data environment in which Foundry is best suited?
For customers within the cloud transformational journey, there is a consolidation activity underway. The question therefore becomes, how can one build operational capabilities?
Palantir can integrate data sources together, and then get to the operational piece to derive value.
For Palantir this is an “and” proposition, not an “or” proposition.
Foundry can be a default SaaS offering, however Palantir can also be deployed as extension to existing clouds, on premise in cloud environments, and across disconnected environments too. Palantir meshes with existing infrastructure and is under control by the organisation that deploys Palantir.
How Foundry makes life of a data scientist easier:
“How can Palantir add value in organic landscape” is the vital question the company needed to solve.
Palantir offers a clear & consistent landscape. The Palantir Chief Architect mentions how Palantir does not want data scientists going through data to build models all day. Instead, the company wants data scientists to truly deliver value within the smallest amount of time. This is vital because, usually data scientists spend 80% of their time going through data to build models.
This changes when using the Palantir OS. This is because, Palantir is focused on Foundry providing a clean consistent hook to the ontology to build models, and Palantir can do this from any environment too.
Data ingestion capabilities, ontology, and combination of CRMs:
Palantir has a value proposition when looking at moving between different domain models, and for each CRM. The question from an organisational perspective is: how can we create an ontology from multiple CRMs?
Hyper Auto is now expanding to integrate across multiple CRMs. A CRM refers to a customer relationship management system in which organisations use to manage customer interactions, support customer relationships and to connect all data from calls, emails and text messages within a team.
Through Hyper Auto expanding to integrate across multiple CRMs this means that connectivity between solutions can happen within hours, in comparison to months or years via conventional manual methods. To add, Palantir OS can interconnect these CRM and generate an ontology of people, places, things and objects in order to derive the best value and insights. Instead of the output being unusable and unreadable, the output is an ontology that can drive business workflows.
Palantir has out-of-box solutions to get going very fast when it comes to CRM operations.
Foundry can become a Hyper-CRM, instead of a layer that just sits on top. It can also be used as a platform to make decisions, and then push those decisions back towards the original CRM. This is valuable for organisations, as it majorly decreases the friction associated with using multiple CRMs, and overall increases the level of productivity and utility that can be derived from data.
How Palantir compares to Snowflake & other individualistic tools:
Palantir is focused on “time to value”. Snowflake is focused on “simplicity”. Time to value meaning, PLTR is focused on efficiencies & reducing cost & time. “Simplicity” meaning the focus on creating a single truth – reducing the complexities of unstructured & structured data.
Snowflake offer a range of different products: “only charging customers for the resources they use.” However, Palantir is focused on “becoming part of the institution we serve”. “PLTR does not sell features, tools, or one off custom applications. When it comes to working with data, those approaches generally work only briefly, if at all”
Snowflake is playing within the data layer area. SNOW benefits from the low barrier to entry: as their products are less invasive. Whereas PLTR is playing within the OS layer – in which their products become the foundation for the business. Palantirs’ products are often viewed as more invasive and holistic.
Overall, Snowflake is offering solutions that are much thinner, and are focused on simplicity. Palantir on the other hand offers a holistic OS that includes 400 different tools, features and custom applications within.
