Organizations need to be data driven with teams that can formulate questions, understand data needed to answer questions, create solutions, validate solutions, and get the insights to the right people in a way they can understand.
The organization needs processes for all to act on the resulting insights. The entire organization needs to become data driven - guided by facts, evidence, statistics and analysis. This is the secret success sauce of Google, Wal Mart, Goldman Sachs, and others.
The challenge for the ‘data scientist’ is to make sense of the randomness - structure chaos into an intelligible pattern or ‘insights’. The challenge for organizations is to structure and establish a common business language that propagates into the data being created by the business.
Transforming into a data-driven organization - turning information into actionable insights is a 3 part strategy:
• Technology – build a modern BI architecture & analytics ecosystem with the right tools
• Processes – streamline and standardize BI processes, measurements, and reports wherever possible
• People – train staff to use BI tools, become data-driven decision makers to meet the needs of the organization
The goal of a modern BI system is to allow the organization to:
• Make confident, data-based decisions based on evidence
• Access timely, relevant information you need, to meet the requirements of all types of users
• Link strategy to execution, leveraging data from all data sources
• Get answers when and where you need them on any device, at any time
• Transform data into actionable insight for everyone
• Uncover new or hidden opportunities to increase competitiveness
• Explore data in an intuitive way, for immediate answers to questions
Three Step OPD Data Science Process:
Step 1. Organize Data.
Organizing data involves the physical storage and format of data and incorporated best practices in data management.
Step 2. Package Data.
Packaging data involves logically manipulating and joining the underlying raw data into a new representation and package.
Step 3. Deliver Data.
Delivering data involves ensuring that the message the data has is being accessed by those that need to hear it.
Plus, at all steps have answers to these questions.
What is being created?
How will it be created?
Who will be involved in creating it?
Why is it to be created
The key is how quickly data can be turned in to currency by:
Analyzing patterns and spotting relationships/trends that enable decisions to be made faster with more precision and confidence.
Identifying actions and bits of information that are out of compliance with company policies can avoid millions in fines.
Proactively reducing the amount of data you pay ($18,750/gigabyte to review in eDiscovery) by identifying only the relevant pieces of information.
Optimizing storage by deleting or offloading non-critical assets to cheaper cloud storage thus saving millions in archive solutions.
We are now living in a data-driven world where a mastery of technologies and processes that enable a rapid ROD (Return on Data) is the key to reducing cost, complexity, risk and increasing the value of your holdings.