Datagraphy or Datalogy?

What is the study of data management best practices?

Do data management professionals study Datagraphy, or Datalogy?


A few of the things that a data management professional studies and applies are

• Tools
• Data Modeling tools
• ETL tools
• Database Management tools
• Procedures 
• Bus Matrix development
• User session facilitation
• Project feedback and tracking
• Methodologies 
• Data Normalization
• Dimensional Modeling
• Data Architecture approaches

These, among many others, are applied to the needs of the business. Our application of these best practices make our enterprises more successful.


What should be the suffix of the word that sums up our body of knowledge?

Both "-graphy" and "logy" make sense, but let's look at these suffixes and their meaning.

-graphy

The wiki page for "-graphy"  says: -graphy is the study, art, practice or occupation of... 

The dictionary entry for "-graphy" says -"a process or form of drawing, writing, representing, recording, describing, etc., or an art or science concerned with such a process"

-logy

The wiki page for  "-logy"  says -logy is the study of ( a subject or body of knowledge).

The dictionary entry for  "-logy" says: a combining form used in the names of sciences or bodies of knowledge. 

Data

The key word that we all focus on is data. 

In a previous blog entry, I wrote a review of the DAMA-DMBOK  which is the Data Management Association Data Management Body Of Knowledge. 


Data Management professionals study and contribute to this body of knowledge. As a data guy, I am inclined to study to works of those who have gone before. I want to both learn from their successes and avoid solutions that have been unsuccessful. 


Some of the writings I study are by people like:  Dan Linstedt,  Len Silverston, Bill Inmon, Ralph Kimball, Karen Lopez, William Mcknight and many others. 

I have seen first hand what happens to a project when expertise from the body of knowledge produced by these professionals has been discarded. It is not pretty. 


Why do I study these particular authors? These folks share their experiences. When I face an intricate problem, I research some of their writings to see what they have done. Some tidbit of expertise they have written about has shed light on many problem I have faced, helping me to find the solution that much sooner.


When I follow their expertise my solutions may still be unique, but the solutions fit into patterns that have already been faced. I am standing on the shoulders of giants when I heed their advice. 


When I am forced to ignore their advice, I struggle, fight and do battle with problems that either should not be solved or certainly not be solved in the manner in which I am forced to solve them. 


Should the study of and contribution to the body of knowledge of data management be called data-graphy or data-logy? 

Datagraphy

The term Datagraphy sums up the study of the data management body of knowledge succintly. 

I refer back to the dictionary definition of the suffix "-graphy": "a process or form of drawing, writing, representing, recording, describing, etc., or an art or science concerned with such a process"

Data is recorded, described, written down,written about, represented (in many ways) and used as a source for many drawings and graphical representations. 


What do you think? I will certainly be using Datagraphy.

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Data is killing us!

Are you drowning in Data?

You have a number of applications collecting various pieces of data in order to run your business. What do you have to do in order for an analyst to make an informed decision?

For the majority of your business operations, dashboards should show current activity. Thresholds can be established for when a particular event takes place and alerts sent automatically. Simulations can be run based on past performance to gauge or even predict the performance of what-if scenarios.

All of these things can be done, the question is: Are they being done?

Image via Wikipedia

Are there so many copies of your application databases, that the cost of servers, disk arrays and storage going through the roof?


Are multiple people required to keep track of which backups and restores are done on a nightly basis driving personnel costs up?


Are business analysts spending more time collecting data than understanding, interpreting and making recommendations, reducing efficiency?


There is a better way.

A person who studies the practices of data management and the applicability of the various data management tools, procedures or methodologies to the needs of the business can make a difference in the use of an organizations data.

This difference can be measured in many ways. It could be an increase in revenue because a relationship was found in the data that could not have been seen before a new business intelligence system was deployed. It could be cost savings of physical equipment.

More often it is the saving of personnel time associated with gathering data just to answer questions.

Some proponents of vendor solutions will suggest that they have all of the answers to your data needs. Perhaps some vendors do have solutions. However, bringing in a vendor solution will not relieve an organization of the responsibility of data management.

The best way to work with vendors is to get them to fully understand all of the pain points associated with your data. No single vendor can solve all problems. Smart people with a vested interest in making your company successful will help you management your data.


Proliferation of data makes an organization stronger. If data is killing you, then you need someone to tame the beast and make data work for you.

Make your data work for you, rather than you work for your data.

Who are the people that will make your data work for you? A database administrator is a good start, many I have spoken to have plenty of ideas for how to make things better.

A data architect is the best start. Data Architects are the people that have studied data management best practices. A great Data Architect can quickly come to an understanding of your pain points and make recommendations that can be done soon to make sure that data works for you.

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Analytical Skills?

One particular skill listed on many job descriptions I have seen gives me more questions than answers.

The skill they would like the candidate to have is listed as : Analytical Skills


How is this quantified? How do you know that someone has analytical skills?


Wiki defines Analysis as the ability to break down a complex topic or substance into smaller parts to gain a better understanding of it.

To what level of detail does this particular job need Analytical Skills? Will the candidate need to analyze the Enterprise accounting functions? Does it need to be the analysis of the physical server infrastructure? Does it need to be organizational layout? Will the candidate be analyzing forensic evidence?

Analytical skill is such a broad topic, and once a person does their analysis what happens to it? Is this a position that has the ability to not just analyze data, but also act on it? Is the analysis required in the position for recommendation purposes, educational purposes, or will the candidate be making decisions based on data provided by others?

Many people have analytical skills, but do they have good analytical skills? Do decision makers listen to and follow their recommendations after an analysis is done?

Data Management professionals are constantly analyzing data. The raw data can represent many diverse topics. Some of the key topics for analysis that come to mind are People, Processes and Things.

People

The analysis of people, their motivations, and their interactions is covered by subjects like anthropology, psychology, sociology and other behavioral sciences. Some people are naturally gifted people readers and can understand others with limited formal training. The analysis of people is useful to many groups within an organization, human resources, marketing, sales, even executive leadership.

Process

There are many types of processes in our lives, a process for getting a drivers license, getting married, fulfilling a product order, shipping a product, and many others. Understanding and recommending improvements to the nature of the processes that we interact with on a daily basis can be very valuable.

Things

Things can be companies, human languages, computer languages, web pages, corporate ledgers, computers, cars, religions, money, inventories, nature. Every "thing" can be studied and analyzed. The more we understand things the more data we generate about those things in order to contribute to human knowledge, self knowledge or our corporate enterprise.

Data

All things that are analyzed have one thing in common. Data. In all analysis data is what is collected, stored, manipulated, reported, recommended and decided upon.

There are best-practices for data management that can assist every type of analysis of every subject. "Pure" analytical skill is seldom used in a vacuum. Databases store data, operational systems collect data, a data warehouse helps in the correlation of data amongst multiple systems that are gathering data. Data Management by its very nature is an analytical skill.

When I see a position for a data management professional that requires analytical skills, I still find it humorous. Because the analytical skills that we can provide in both our own analysis and in guiding the analysis of others should go without saying.

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Data Management Industry?

How important is an industry classification for data management professionals?

I have been asked  the question: What is your industry?

My reply, when given the option, is to say the Data Management Industry.

The particular vertical market that my company classifies itself according to Dun and Bradstreet Industry classification, Standard Industry Classification (SIC) or even North American Industry Classification System (NAICS) has a limited impact on my day to day duties.

Some industries have a more stringent requirement for data quality or data availability than others, but overall the manner in which data is managed between industries is consistently similar.

In every industry I have worked the same process is generally followed.

Data is captured

In Telecommunication, Energy and Supply Chain these systems are usually automated data capture via a field device such as a switch or a sensor, some are driven based on orders and some are driven based on consumer behavior.

In Retail and ECommerce the source data capture component is a customer facing system such as a web site or scanner for checking out at a grocery store.

Most companies have a human resources system that keep track of time for the customer facing employees tracking contextual information such as when did an employee arrive, what did they work on, when did they leave?

Data is integrated

Once we have the source data and as much contextual information about this data captured; that data is transferred to another system. This system could be a billing, payroll, time keeping or analytical system, such as a data warehouse or a data mart. The methods used to create this integration system can vary depending on the number of source systems involved and the requirements for cross referencing the data from one system with the data in other systems.

At times certain data points are transferred outside the organization. This data could be going to suppliers, vendors, customers or even external reporting analysts.

Internally each department within an organization needs to see certain data points. Marketing, Merchandising, Finance, Accounting, Legal, Human Resources, Billing, to name a few do not necessarily need to see all of the data captured. However the data they do require does need to get to them in a timely manner in order for these departments to support the overall organization.

Data is protected

During all of these data interchanges the same types of functions need to be performed.

Data must be secured (the users that need access have it, those that do not need access cannot see it), backed up, restores tested and verified, performance must be optimized, problems need to be addressed when they arise, quality must be maintained, and delivery must be verified.

Data Management Professionals

The Data Management profession consists of people striving to create, implement, maintain and evolve best practices for managing the data that runs our enterprise.

The challenges of data management, the problems we solve and the solutions we provide are more similar than they are different.

Is the industry classification of the enterprise we support all that important?

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Thought leadership

You have to be a thought leader in order to recognize one.

I hear the term thought leader bestowed upon people occasionally. I have even bestowed this term on some people that I consider to be extremely knowledgeable about building data warehouse systems.

The wealth of information for data management best practices continues to grow. Thought leaders can publish knowledge about solving a particular problem in a variety of forums now: blogs, books, articles, and even research papers. The sheer volume of information about the "best practices" is almost intimidating.

The ability to take in all of the information about best practices for a subject area, apply it to the situation at hand, consolidating the recommendations from multiple sources as well as ignoring those recommendations that are not applicable make you a thought leader. Google provides a way of finding a site that answers a particular question. If a person does not ask the correct question, Google does not provide a good answer. Once Google finds a particular answer to a keyword query you have to apply that answer to your particular situation.

Let us take a specific example.

The question should not be:

What is the best way to build A data warehouse?

The question should be:

What is the best way to build THIS data warehouse?

Even something as simple as learning a how to apply a new SQL trick that you learned to a specific problem you are working on shows the application of this knowledge. Best practices can be abstract, or even theoretical. When you can take recommendations from many sources and apply their expertise to your specific problem you have taken a big step.

This can apply to many other professional areas.  SEO, Business Analysis, Business Process Re-engineering, ETL development,Resume writing, Financial Analysis, Online Marketing,  etc...


If you can study multiple sources and apply their recommendations or findings to your own situation, you become a thought leader.

You become a recognized thought leader when you write about it. 

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