• THE 3AG GUIDE TO

    DATA ENGINEERING

     
     
    In this comprehensive guide, we look at all
    aspects of data engineering, which together
    form the foundation for all things data.

    Illustration of a cog and a data block, indicating that the 3AG Guide to Data Engineering provides insight into the moving pieces, or nuts and bolts, ot data engineering for manufacturing, mining, and other companies.
  • Introduction to

    data engineering

     
     

    What is data engineering? And why does it matter?

    Illustration of two open instruction manuals introducing businesses to the power of data collection, data engineering, data analysis, and data sharing.,

    Perhaps this is best explained with a metaphor. Imagine it’s 1970, and you’ve just opened a bookstore. For the grand opening, you stock the 10 most popular books from the New York Times bestseller list, but soon realize customers are looking for other books in addition to the most popular ones. You add books from the top 20, then the top 100.

     

    But now customers get confused when they enter the store, because you’ve gone from stacking books in 10 piles to stacking them in 20 and then 100 different piles. Worse yet, customers start mixing the different piles, which makes it even harder for them to find what they want.

     

    So, you add a system of bookshelves, putting the books in order of popularity. Customers entering the store can now walk past the most popular books and make their way to the slowest sellers.

     

    But then certain customers ask you to make special orders.

    You decide that it makes sense to order a few extra since it’s a sure sign of demand.

     

    See a pattern here? This constant improvement and iteration of the organization of bookstore data has strong parallels to the discipline of data engineering.

     

    Data engineers are charged with helping their companies organize data to be not only accessible to the widest audience, but also to be useful for their particular needs. Some employees just need to look at a chart. Others need to do comprehensive analysis. And other employees need to structure data to allow for advanced use cases like machine learning and artificial intelligence.

     

    Data engineering makes this possible, while also dealing with ever-changing internal and external business landscapes.

    Learn more

  • Image of a sensor-connected and data-enabled residential building as a metaphor for how data engineering provides information about every aspect of business activity in material and virtual environments.

    Why consider

    data engineering?

     
     

    Another metaphor will help. 

    Imagine your company owns either a shed, a house, a multi-family complex, or a high-rise. The shed owner probably doesn’t spend much time thinking about engineering permits or maintenance since they don’t need to worry about services like heating, running water, or electricity. And if the shed won’t be upgraded anytime soon, there's no need to plan for future changes.

     

    The house owner will need to devote significantly more effort to keeping things running; even so, they won’t need to concern themselves with more than their own and their family's needs.

     

    A multi-family complex requires more planning, more resource integration, and a more structured approach to handling issues as they arise; and different tenants may have very different needs.

     

    And a high-rise tower will have a completely different set of engineering requirements, permitting requirements, safety requirements, and so on.

     

    The high-rise will also be much more complicated to manage, particularly if things like fixtures have not been standardized throughout the building.

     

    See a trend here? The more complicated the structure, the greater the need for better infrastructure. And earlier planning becomes even more important for bigger buildings, as early mistakes and omissions can become costly later on.

     

    The same holds true for data engineering within a company. While the smallest companies may not immediately need tools and structures to support data access, companies with growth aspirations will need to consider this issue. And the longer they wait, the more expensive the effort will be, with more work required to fix past errors and omissions.

    Learn more

  • Developing a

    data strategy

    A neon sign-style image with the words Data Coach, surrounded by symbols of data and connectivity.

    Without a clear data strategy, companies risk carving off small data projects (or no projects at all) that don’t connect, either to one another or to their central databases.

    Forward-thinking companies see the value of knowing both where they are, and where they want to go, on their data journey. From a data perspective, this involves understanding where they fit into the analytics maturity model.

    Analytics maturity graph showing all phases of data engineering: descriptive, diagnostic, predictive, prescriptive.

    Most companies that haven't formally developed a data strategy tend to fall in the descriptive category, performing basic reporting. Those that consciously decide to focus on improving their reporting advance to the diagnostic phase, where they not only centralize data to improve reporting efficiency, but also ask “why” when doing analysis. More advanced stages of maturity include predictive and prescriptive, but few companies achieve this level of expertise across the entire organization.

     

    Common mistakes many companies make include jumping into advanced use cases without getting the basics right, or starting to plan before knowing what analytics maturity stage they're at.

    Skipping steps can mean missing lower-hanging opportunities for improvement. Such haste can set a company up for failure if begins projects not built on a solid foundation of earlier stage prerequisites.

     

    For example, a company looking to do predictive analysis to support production planning won't be able to efficiently or reliably perform analysis if source data is spread across hundreds of spreadsheets managed by dozens of people.

     

    At 3AG, we developed the Data Coach specifically to help companies assess their current analytics maturity level, their targets, and the steps required to succeed.

    Learn more

  • Data governance

    Data governance is the work of setting your company's policies on how it collects data. It is tightly integrated with data strategy, which includes defing and implementing data governance rules.

     

    A solid data governance policy will not only identify which sources to consolidate, but will also define who can access data, when data is pulled, and what to do if conflicts occur. Governance policy also addresses other issues, such as retention and integrating new data sources as they come online.

  • Wrapping up

    Data engineering is a complex topic, made more so by the countless ways organizations can tackle it.

     

    For organizations looking to gain more control over their data but lack experience in this area, a guide is invaluable.

     

    Consider bringing in experts who can give an unbiased assessment of your current situation. We would be honoured if you were to consider 3AG's Data Coach as your best option.

     

    Sample of a 3AG Data Coach report outlining how businesses can develop and achieve unique data engineering infrastructure to make the most of their data and thrive in a competitive market.
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Privacy Policy
We collect personal information from our customers in the regular course of doing business. This brochure answers some of your most frequently asked questions, and lets you know exactly how we're protecting the information you entrust to us.


What personal information do you collect about me?

We collect the following information about you:
-Name
-Email Address
-Payment card number
-Payment card expiry date
-Purchase history
-Product/service preferences
-Customer satisfaction info
-Opinions about products and services

When you visit our web site, we also collect:
-information about your computer, including your IP address, the type of operating system and browser you use, and your computer's location
-what pages you visit on our site and what links you click on
-what other sites you've visited recently


How do you use this information?

The main reasons we collect personal information from you are:
-Customer service
-Marketing
-To complete a sale/transaction

If it's a necessary part of any of these transactions, we may disclose your information to another company. For example, when you apply for credit, we pass on your personal information to a credit reporting agency so we can complete a credit check. We also pass on your name and address to a courier company to complete a delivery.


Use of Personal Information for Secondary Reasons

We also may use your personal information for other, secondary reasons, including:

To complete a sale/transaction
-Name
-Email Address
-Payment card number
-Payment card expiry date
-Purchase history
-Product/service preferences

Marketing
-Name
-Email Address
-Purchase history
-Product/service preferences
-Customer satisfaction info
-Opinions about products and services

Customer service
-Name
-Email Address
-Purchase history
-Product/service preferences


Sharing of Personal Information with Third Parties

Sometimes, we also share your personal information with other companies, including:
-Partners

We will also disclose your personal information if we are required by law to do so.



How do you get my consent?

When you provide us with personal information to complete a transaction, verify your credit card, place an order, arrange for a delivery or return a purchase, we assume you consent to our collecting it and using it for that specific reason only.

If we ask you for personal information for a secondary reason, like marketing, we will either ask you directly for your consent or provide you with an opportunity to say no. Saying no is called "opting out". By opting out, you can tell us not to collect the information and/or not to share it with other companies.



How do I opt out?

Contact email us at privacy@3agsystems.com with the subject line "Opt out".



How do I get more information?

Our staff will be happy to answer any questions you may have about your personal information. If you would like more information about our policies, or you would like to see exactly what personal information we have about you in our records, or you wish to register a complaint, please contact:

Email: privacy@3agsystems.com

You can also contact the Privacy Commissioner of Canada for assistance between the hours of 8:30 a.m. to 4:30 p.m. est, at:

Toll-free: 1-800-282-1376
Phone: (819)994-5444
Fax: (819)994-5424
TTY: (819)994-6591

or by mail at:

30 Victoria Street
Gatineau, Quebec
K1A 1H3

or on the web at:

http://www.priv.gc.ca