What is Data Analytics
Understand Key Product Value Delivery
also: Iterate on SWE's Backend Design Processes
What is Data Analytics
Data analytics is the process of examining raw data to uncover patterns, trends, and insights required to make informed decisions. Typically our clients are “software enabled” and are generating more information than could ever be organized or crunched with spreadsheets - software, cerebral design, and advanced methods are required. Data analytics work begins with raw information collection and reporting, and in its fully-fledged state is a key shaper of strategic roadmaps across all departments
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Data Analytics - What is it?What is Data Infrastructure
Data infrastructure is the tools and systems that allow organizations to collect, store, manage, process, access, and serve data. Plug-and-play data infrastructure vendors have multiplied in recent years, but specialist engineers are still required for more advanced/custom requirements, complex vendor implementation, and bridging gaps with SWE.
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Data InfrastructureWhat is AI
What is AI
What is AI
AI (Artificial Intelligence) is a technology that enables machines to mimic human intelligence, allowing them to perform tasks like understanding language, recognizing images, or making decisions. Machine Learning is an older but more mature subset of AI - when its capabilities are sufficient for a problem, ML is more straightforward, definite, quick to develop, and supported by tools/vendors/automations.
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Practical AIFoundations
Integrate Data team into backend design+implementation+UAT processes as well as vendor selection + implementation. Transfer ownership of raw data management and entity design. Straighten out initial reporting and codify key product health frameworks. Experimentation improvements.
Strategy
Undertake deep-dives with product team to understand product strengths and opportunities. Develop data sources outside of the main platform to really understand what the key value is that customers are looking for. Develop frameworks used to understand user behavior and product success.
N.B. Product departments are often the group that require Flatiron’s most creative talent.
N.B. Product departments are often the group that require Flatiron’s most creative talent.
Intelligent Product Features
Experience personalization, operations automation, experience streamlining, user delight via Practical AI
Case Study:
Incline3
Dandy Data went from 0->35 in 1.5 years, though most client teams follow a more modulated trajectory...
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Incline2
Flatiron has a number of partnership models, including fully embedding our teams into a company or seeding the company’s data team...
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Incline
We’ve built industry-leading functions from scratch at top-tier unicorns (Ro, Dandy) in record time...
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