DT 4 Data chapter 4

9 flashcards · Programming Languages · by Daniel F.

1. how digital transformation changes turning data into assets

2. 5 principles in developing a data strategy

   Gather diverse data types Use data as a predictive layer in decision making Apply data to new product innovation: data can power your existing products or you can innovate more quickly and cheaply Watch what customers do, not what they say: use behavioral data Combine data across silos: find connections in separate data

3. 3 trends in big data

   Analyze unstructured data Apply new tools Use cloud computing Volume, Velocity Variety

4. Unstructured data

   information that is recorded but doesn’t fit easily into neat forms social media data location data new sensors in every device

5. Tools to Wrestle Unstructured Data

   machine learning natural language processing

6. 3 Myths of Big Data

   The algorithm will figure it out Correlation is all that matters (spotting a pattern is not (always) enough). All the good data is big data (in many cases, companies can build valuable data assets and apply them to strategic ends without delving into messy world of big data).

7. Where to Find the Data you Need

   Customer data exchanges invite customers to contribute data as part of interacting with your business or in direct exchange for value you offer them Lead users most important input Supply chain partners Public data sets social media, gov data Purchase or exchange agreements buy competitor's data

8. how to turn customer data into business value

   Insights: reveal invisible relationships, customer psychology, customer behavior, and the impact of decisions on the former Targeting: target the most relevant audiences Personalization: tailor the product, messaging, offers, pricing, services to each customer Context: providing a reference frame for decisions and identify future hazards

9. Tool: The Data Value Generator

   The Data Value Generator is a tool for developing a data strategy Area of Impact and Key Performance Indicators: Define the specific area of your business that you want to improve through a new data initiative. Identify your primary business objectives within that area. Value Template Selection: Choose a value template (Insight, Targeting, Personalization, or Context) to guide your data strategy. Concept Generation: Use the selected value template to brainstorm specific ways that data can provi…