BigInsights

My # 1 recommendation is to try things, and fail fast...

Process Optimization, Business Leadership, Technology Optimization

if you can walk before you run, you will win

scan .bash_history for repetitive commands, automate those.

Top 3: 1. Practice Agile PM Method. 2. Move to the Cloud. 3. Utilize Corporate Data Pyramid (CDP)

Choose a platform to "play" on that you can build up quickly, that does not cost a lot, but you know you can expand if what you are doing yields fruit

My first recommendation is for an enterprise to provide real-time, contextualized decision support resources to all personnel. Agility is the ability to make the best evidence-driven decision on the fly.

Top 3 Recommendations - Process, Business, Technology Optimization - Walk and Then Run

move away from "cargo cult" agile where you say agile words then do waterfall.

i also think that design thinking allows you to quickly show value, in quick spurts

Try, adjust, improve, try again.

think in terms of a platform and automate everything

@jameskobielus your viewpoint is correct but leaders do not listen

This is a neat, quick intro to design thinking.. http://dschool.stanf... Something we use at IBM.

avoid human-based processes, it should be software defined. Also destroy all printers.

Even in 2016 we are still in "data silo" mode. Time to break that habit. #Hadoop is a great platform for this purpose since it holds all data.

My second recommendation is for an enterprise to provide a collaborative environment within which employees can share their best data, analytics, and insights rapidly to respond to new challenges. Agility = fast brainstorming.

@drumbum25 Platform is only technology Rohan, we need to improve process and leadership

Utilize Just Enough Governance (JEG) techniques to make rapidly available as needed.

Crowdsource within the Enterprise, it helps improve collaboration, which helps transformation. All of this from process, business leadership and technology perspective

@datagenius Seems like we have a real problem with leaders listening across the board these days...

@AyleeNielsen Yes that is a fact and often human ego does not agree

bring analytics closer to the user, embrace new technologies and agree with the experiment/fail fast

my top recommendation is to use the cloud

@joe_caserta Governance is a leadership lesson and we need more to understand this. Agree

My third recomm is for an enterprise to build their decision support and collab environment on a self-service cloud-based data platform that leverages Hadoop, stream computing, and NoSQL. Agility = cloud-based process flexibility

Three goals for data: Ingest, Discover, Leverage

Speaking of Data Silos, I saw a great quote recently.

"You don't really know the value of data before you have it. Data is an investment, but once you have it, you can do amazing things".

@DwaineSnow failing is something we should embrace in business and in life. No better way to learn

@datagenius Platform in the sense of organising ur business outcomes. How u implement it is technology.

@jsnburns - Agree 100%. My wife would say I embrace it all the time :-)

if we do not listen we do not learn, if we do not learn we do not optimize and if we do not optimize we do not succeed.

Yes @dwainesnow -- what do you even have to work with? Get it in a data lake so you can begin trying to find gems of competitive advantage in it.

Add CrowdChat to your data team toolbox to generate ideas :)

@drumbum25 True and always keep the message going

@joe_caserta love this: Ingest, discover , leverage

You only asked for 3, but my 4th recommendation is for enterprise to institute data-science-driven real-world experiments across all business processes, customer-facing, internal, and B2B, so you can fail fast and iterate 24x7.

Moving to the cloud is definitely the #1 way to increase agility

uninstall all non-web based tools. (i.e. office, any chat tools that aren't web-based, etc)

Tip: Abandon idea that all data must be structured to be analyzed.

@JimWankowski Agree! No infrastructure to deal with! Makes you much more agile.

@DataWH_News With today's technology, like Spark, you do not even have to wait to get it into a data lake. That might make things easier, or faster for exploration, but you do not need to wait for that...

Spark is the primary tool that interacts with the Lake.

@joe_caserta Spark is The Analytics Operating System.

@DwaineSnow - Good point but can you elaborate?

@DataWH_News Sure - Spark by itself is a processing engine (like an OS). It can read the data from wherever it is stored (the file system) and process it.

Allow flexibility for team members to explore and investigate, streamline decision making processes, and avoid micromanaging projects

Spark does not care what format the data is written in, or what language you use to get insight from the data

Spark allows you to quickly access, join, correlate, analyze, predict, and optimize results based on ALL of your data - no matter where it is stored, or what format it is in.

educate yourself and your team about the cloud ... There're a lot of options from just infrastructure e.g. Softlayer to fully managed services e.g. Bluemix services. Experiment and then decide instead of just reading abt them

AND - Spark can be used in your Hadoop cluster (on premises or on the cloud, since it is one of the core Apache Hadoop components) or in a standalone cluster

@DwaineSnow So it doesn't immediately need the data in a lake to leverage it all together for deeper insights. Data lake might be good for longer term but Spark starts you right away. Cool.

@joe_caserta I forget the exact stat ... but some vast majority of data is unstructured! That's a lot of dark #bigdata.

@DataWH_News Right on.. You can explore and find the value before you start storing the data.