dama webinar: the theory of everything - is it time to rethink data management?

The Theory of EverythingIs it Time to Rethink

Image © Thomas Leuthard

The best source of knowledge is experience

Data Management?

Your Presenter

•  Founder of Equillian •  Experts in Enterprise Information Management •  Three founding values –  Independence –  Passion –  Knowledge

•  Jon Evans •  Information Strategist •  Self-confessed Data Quality geek •  @MadAboutData

Image © Thomas Leuthard


Data or information?

WWW. E Q U I L L I A N . C O M 5!

In the blue corner… In the red corner…

The “data-philes” The “info-holics”

Data Asset Data Quality

Data Governance Data Architecture

….. ….. …..

And it doesn’t stop there…


Information Asset Information Quality

Information Governance Information Architecture

….. ….. …..

Is it any wonder our stakeholders are confused?

The quality of our data ultimately affects the quality of our decisions

The Data Value Chain

•  Data is the digital representation of objects and events (“raw input”) •  Information is data that has been collated and organised (“data in context”) •  Knowledge is the understanding we derive through interpreting information (“insight”) •  Decisions are the judgements we make based on our acquired knowledge (“outcomes”)


Data Information Knowledge Decision

is collated from

is derived from

is based on

Raw Refined

The quality of our data ultimately affects the quality of our decisions

An Example

•  Data is the digital representation of objects and events (“raw input”) •  Information is data that has been collated and organised (“data in context”) •  Knowledge is the understanding we derive through interpreting information (“insight”) •  Decisions are the judgements we make based on our acquired knowledge (“outcomes”)



is collated from

is derived from

is based on

21, 6, 2016 Today’s date is 21st June 2016

My summer break is only 4 weeks away

I’d better book my flights and hotel

Data versus Information


Data Information

is collated from

•  Raw •  Limited context •  Implicit relationships

•  Processed •  Meaningful context •  Explicit relationships

That’s settled then – information is simply data that’s been through a degree of processing to make it more useful

So at what point does data become information?


A file containing raw sales figures

A formatted report that lists sales figures ordered by territory

A formatted report that compares sales performance across different territories

Data Information


The Data Continuum

Raw Refined

Data Information




Two Different Perspectives





It’s all just data, but some is more processed

It’s all information, but some is just more usable

The Machine Perspective

The Human Perspective

•  Humans operate in the information world

•  When we see data, our brains sub-consciously convert it to information

It’s time to think differently…We have two parallel and co-existent worlds – the data world and the information world

•  Machines operate in the data world

•  We use them to store data so we can readily access it as information

•  Information is simply the human interpretation of data •  To a machine, your sophisticated sales report is just data •  To a human, a set of raw sales figures is still information

If a tree falls in a forest and no one is around to hear

it, does it make a sound?

If data is stored on a computer and no one ever sees it, is it information?



Raw Refined

Information (Continuum) Knowledge Decision

Data (Continuum) Knowledge Decision

Raw Refined


So where does that leave us?

Do we need to change our vocabulary?


INFOVERSITY

Data ? No, let’s just agree that we’re talking about exactly the same thing from slightly different perspectives

Image © D. Sharon Pruitt


What about unstructured data?

What is unstructured data?•  Data that has no structure?

•  Documents & reports?

•  Audio & video?


OK, so what is structured data?•  Data that’s stored in

a relational database?

But surely all data has some structure

But all documents are structured to some degree and even language

follows the structural rules of grammar

But don’t media files conform to defined standards and include structured meta-data?

But there lots of alternative approaches to storing data nowadays, and I wouldn’t

describe them as unstructured…

Oh dear, have we confused matters again?


A database table containing monthly

sales figures

An extract of the monthly sales figures saved as an Excel file

The monthly board report, which shows a table of monthly sales

figures on page 6

Structured Unstructured


The Data Continuum

Firm structure Fluid structure

Structured Unstructured


sales figures


figures on page 6


The Data Continuum


Raw

R

efine

d

Firm Fluid


sales figures


figures on page 6





Raw

R

efine

d

Firm Fluid


sales figures


figures on page 6




Which of these would you want to avoid falling into the hands of a competitor?

So is there such a thing as unstructured data?

Or are we just managing a continuum of data?

Maybe we should ask a couple of our employees…

Bill (Database Administrator) Betty (Records Manager)

I look after my company’s documents and files – I don’t really get involved with data

When I joined, we kept lots of our information on paper…and still do…

…so I quickly learned the importance of only keeping the stuff we really need

I look after my company’s databases – I don’t really get involved with documents

When I joined, we only had one server and I kept a close watch on disk space…

…but now hardware is so cheap, if we run out of storage, we just buy more!

Images © Thomas Leuthard

It’s time to think differently…


We’ve created an artificial and

unhelpful separation of structured and unstructured data

We need to cross-pollinate our skills and knowledge to bring them back together again

Just because storage is cheap doesn’t mean we

can do without a retention and archiving strategy

Just because we use SharePoint doesn’t mean

we can avoid defining our document standards




Raw Refined


What is knowledge?•  “the understanding we derive through interpreting information”

•  “information and skills acquired through experience or education” •  It’s the documented (and undocumented) “learnings” that tell us how

to run our business

•  Includes methods, procedures, best practice, patents, trade secrets…



Raw Refined


Knowledge Management is so often the poor relation of Data Management •  “it’s all in people’s heads so there’s nothing to manage” •  “we have a folder somewhere that contains all the

procedures” •  “we don’t really have a formal approach – everyone

looks after their own stuff”

How well do you manage the knowledge in your organisation?



Raw Refined

Information (Continuum) Knowledge Decision Decision Information (Continuum)

Data (Continuum) Knowledge Decision

Raw Refined

Decision Data (Continuum)

Solution: just manage it in the same way as your other information assets

Image © Jenny Downing


Where does big data fit in?

n. data

big data

Image © Eric Fischer

The Data Continuum


Raw

R

efine

d

Firm Fluid

The data continuum isn’t limited to 2 dimensions – we could include volume, velocity, variety…

It’s time to think differently…Ultimately, it doesn’t matter whether our data is big or small, firm or fluid, raw or refined

In all cases we need… •  Good definitions so we understand what we’re dealing with •  Clear processes for managing it through its lifecycle •  Sophisticated techniques for exploiting its value •  Strong governance to ensure it’s being treated as an asset •  A robust technical infrastructure to support all of the above


Data Architecture Management

Data Development

Data Operations

Management

Data Security

Management

Reference & Master Data Management

Data Warehousing & Business Intelligence

Management

Document & Content

Management

Meta-Data Management

Data Quality Management

Data Governance

DMBoK wheel courtesy of DAMA International



Data Development

Data Operations

Management

Data Security

Management



Management

Document & Content

Management



Data Governance

Governance

Exploitation

Management

Definition

Infrastructure

DMBoK wheel courtesy of DAMA International

Round is the perfect shape for many things…


but unfortunately, data management isn’t perfect

The DAMA Square?


Data Governance


Dat

a O

pera

tions

Man

agem

ent

Dat

a Se

curit

y M

anag

emen

t

Dat

a D

evel

opm

ent



Document & Content

Management


Data Exploitation

Data Management

Data Definition

Data Governance

Data Infrastructure


I like the symmetry of the wheel, but prefer the transparency of the square


Data Governance


Dat

a O

pera

tions

Man

agem

ent

Dat

a Se

curit

y M

anag

emen

t

Dat

a D

evel

opm

ent



Document & Content

Management


Data Exploitation

Data Management

Data Definition

Data Governance

Data Infrastructure


We need to formalise our data

quality policies, standards, roles

and responsibilities

We need to ensure the data definitions and

data quality rules are documented

We need to identify the structure,

location and flow of data to guide our data quality efforts

Enablers

Improved data quality leads to more accurate

insight and better decision making

Beneficiaries High quality master and reference data helps to

improve consistency and simplify integration

Data Quality in Context



Is our strategy working?

Military Strategy“The planning, coordination, and general

direction of military activities to meet overall political and military objectives”


Data Strategy“The planning, coordination, and general

direction of data activities to meet overall business objectives”


Developing a Data Strategy•  Step 1 – Conduct a data management maturity

assessment •  Step 2 – Determine that the overall maturity is extremely

low (just like everyone else) •  Step 3 – Endure a painful meeting with senior execs

where the full enormity of the challenge is laid bare •  Step 4 – Agree some short term tactical fixes, because

anything else is deemed too difficult •  Step 5 – Return to your desk, cry into your coffee and

carry on as before


Sound familiar?

It’s time to think differently…A strategy… •  is a plan of activities to get

us from the current state to a desired future state

•  is often clouded by negative perceptions of our starting point

•  can sometimes turn into nothing more than a series of short-term tactical fixes

•  ideally needs to be driven by a high-level business vision

A vision… •  is a picture of our desired

future state created by the business

•  focuses on our future aspirations, rather than our current issues

•  takes a long-term view, which can be broken down into interim milestones

•  provides the basis for a more detailed strategy aligned with our business

Don’t start your strategy until you’ve developed your vision

Developing a Data Vision•  Step 1 – Engage with key stakeholders to understand the

future role of data from a business perspective •  Step 2 – Analyse the business drivers, opportunities and

challenges to identify a set of underlying themes •  Step 3 – Switch negatives to positives and craft a description

of a brighter future that aligns with each of themes •  Step 4 – Present your themes to senior execs using imagery

and metaphors to bring your vision alive •  Step 5 – Agree that it will take sustained effort to realise the

vision and carve each theme into interim milestones •  Step 6 – Keep the vision at the forefront as you develop it

into a fully fledged strategy




Is it time for a rethink?

Information is simply our interpretation

of the complex world around us

But in our rush to push the limits of achievement and embrace the possibilities, we’ve confused our thinking and created artificial barriers where none should exist

At the end of the day, it doesn’t matter whether data is big or small, firm or fluid, raw or refined, created by man or created by machine – data is just data

Our technology might have advanced, but our goal remains the same – a unified

approach to governing, defining, managing and exploiting

our data

Digitising information and using computers to store it as data have helped us achieve things

we never thought were possible even 10 years ago

Training changes the way people act Education changes the way people think

WWW.EQU I L L I AN . COM

[email protected] @MadAboutData