CIO: what's in it

Objective:

His objective is to increase data/information fluidity and accuratie in the company.  By fluidity mean the right information to the right people:

Right information: not just content but grain, frequency, medium of provision

Right people:

• ·         Data analyst: role is to pre-chew data and provide added value analysis to decision makers. Added value analysis is not just what but why, so what and what to do with it
• ·         Data scientist: role is to explore the data to find patterns using analytical tools (functions/formulas). Will perform both descriptive analysis (look at past events to perform segmentation, correlation, clustering, multi variate analysis) or predictive (build models to predict the future with regression, decision tree)
• ·         Business audience:
• o   Product managers
• o   CRM
• o   Marketing team
• o   Finance
• o   Ops
• ·         Executive: need summarize yesterday data to track health of business vs projections/target and LY + create finance model for new opportunities

Role:

CIO role is to set the strategy appropriate to the maturity of the company, make it evolve and grow with the company.Strategy is around not just tools but as well teams and skill sets and infrastructure.

Why is it important to have a CIO?

Need to have a consistent and centralize data roadmap, enforce one data truth. If it is spread leads to growing pain
Once company reach a certain size then analysts and data scientists can be decentralize to business. CIO office is then just a service provider and is pure IT.

Team:

• DWH: nucleus  of the data, where it is stored. Need a data acquisition team + Architect + Administrators Presentation team: In charge of distributing the data to the audience whether in the form of report dashboards or data sets
• Data analyst: primary consumer, provide the added value on top of data
• Data scientists

What would be the right organization for 150 people company today?

Cheap efficient fast turn-around.

• Cheap: Plethora of free tools with Adoop/Hive/R and mySQL, or tools included in corporate licenses (Microsoft SQL servers with Analysis studio, PowerPivot etc) or cheap solution
• Efficient: don’t address the enterprise approach in its entirety: create a robust, clean and agile DWH and plug on top departemental solution like Tableau, Quilk.
• Fast turn-around: easy to learn, easy to maintain no deployment.

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Technical
Architecture
Culture

Stored in one location, is clean, accurate and available on time.
Distribution of the data