Hi, I’m Yulia Kosarenko, and you are watching the Why Change channel.
Our topic this time is data – and whether it’s important for business analysis.
This topic comes up more and more often, and no surprise.
Organizations create data at neck-breaking speed –
and often it results in more data than they can manage.
Did you know, for example, that more than 80% of all data generated today is big data?
What’s big data? What do you do with it?
This is exactly why we need to have more conversations about it.
Every business application, device, website and social media platform
generates data that can be used (or abused).
Without intelligent data management practices,
organizations are not able to take advantage of their data
and eventually may lose any competitive advantage they’ve had.
They can even fall victim to hacking attempts and ransomware.
And these are not only concerns for security experts and data architects.
Business analysts play a central role in defining requirements for organizational changes –
and it’s not possible to do that without considering data.
Data connects business processes and the parts of an organization
to create an integrated enterprise.
Every single business change involves changing business data:
creating new data, sharing it, using it to make decisions
or to store information for future use.
We cannot analyze business processes
and disregard the data that these processes will use or update.
We need data to develop the right products,
connect to our customers at the right time,
to run the business effectively.
We need data to detect process inefficiencies,
learn the patterns of customer behaviour
and understand, or even better, predict their needs.
And just as importantly, organizations need to use data to make business decisions.
If you truly want to help your clients solve business problems,
you need to focus on helping them make better decisions based on
clean, consistent, conformed, current, and comprehensive data.
This means producing useful business analytics insights.
To do that, we need business analysis –
to understand the problem that needs to be solved,
what data is required to produce the insights
and to properly define analytics requirements.
So a business analyst needs to understand
the fundamentals of data management and data analysis
to provide value to modern data-driven enterprises.
In this video, I will share with you what business analysts need to know about data.
First, the basics: what is data, in what forms it exists,
where it can be stored and how it may be structured. Then, the types of data.
You need to understand the difference between structured and unstructured data,
and while we are at it, what is semi-structured.
The methods and technologies for handling structured and unstructured data can be quite different.
In particular, we cannot use traditional methods, such as relational databases,
to store and manage unstructured data.
Next, you must be able to distinguish quantitative and qualitative data
and be clear about the difference between nominal and ordinal categorical data.
What is discrete data, and what is continuous? Numeric or text?
How can we capture dates and times?
Is there a difference between a flag and a code?
And what exactly does it mean, XML data?
Next, as a business analyst you need to understand the data lifecycle:
what happens with data as it gets created, moves around, is transformed,
restructured, used, shared, and eventually destroyed.
At every stage of the data life cycle,
there need to be requirements related to managing the data.
For example, how to ensure that the data entered by end-users is valid and accurate –
how can we validate data inputs?
How can we share data from one business system to another?
And what happens if these two systems have different definitions and data structures?
How can your organization use external data to its advantage,
for example, customer reviews collected on social media, or consumer research from third parties?
What data do you need to ensure customers receive
accurate notifications about their orders or product updates?
What data needs to be protected? Encrypted?
And what data about your customer you should destroy at a certain point
to reduce the risk of exposure – both for the customer and for your company?
When you start to analyze these requirements for managing, using and sharing data,
you will discover that you also need additional tools and techniques to help you.
This could be creating data models
to help capture the main concepts and relationships between them.
An ability to create a conceptual data model is a very valuable skill –
and can help you in your own professional growth.
Understanding how data is structured in relational databases,
what are data entities, relationships and attributes
would be key if you were to work on a data warehousing or business intelligence project.
Basic SQL knowledge can make you a powerhouse on your team.
Imagine what you could do if you were able to explore and query data
to validate various scenarios, detect exceptional flows,
or resolve arguments between stakeholders with production data in hand.
Another important skill is ability to describe the data.
Every term, data entity and attribute need to be defined.
You may have done the basic version of it as a glossary.
From there, if you can define the data type of each attribute,
what are the valid values and business rules, you can contribute to a data dictionary.
This is necessary to promote consistent use of data across the enterprise –
to start governing the data.
Senior business analysts are often key contributors to their organizations’ data governance efforts.
And if you can create a data dictionary, then you could also work on data mapping,
to support the integration requirements.
Every business application these days is integrated with at least one,
and sometimes many others.
Integration requires that the data from one system (the source)
is mapped to the data in the target system, to ensure correct data transit and transformation.
Someone has to do the mapping – when it is inaccurate or incomplete,
this becomes a frequent reason for integration failures.
When a business analyst has a good understanding of business data,
its sources and the rules about managing it,
this knowledge will be invaluable for accurate data mapping.
And if you know how to do it, and have practical experience,
your value as a professional, again, will also grow.
Of course, this is not the end.
A business analyst that masters these fundamental data management skills
can continue to develop their competencies further.
Data exploration, analysis and visualization, analytics and business intelligence
are key capabilities that data-driven enterprises are keen to develop.
As a business analyst, you have the foundation to support these capabilities,
and grow professionally as you learn more and more about
data management, governance, and analytics.
I will include some links in the video description if you would like to learn more.
For organizations, please take a look at the corporate training offerings
on my website why-change.com or contact me directly.
And if you are a business analyst, remember
the twelfth principle of the BA mindset – learn, adapt, and thrive!
Thank you very much for watching, and until next time.
This is Why Change channel. Bye-bye.