What is involved in Data Engineering
Find out what the related areas are that Data Engineering connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Data Engineering thinking-frame.
How far is your company on its Data Engineering journey?
Take this short survey to gauge your organization’s progress toward Data Engineering leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which Data Engineering related domains to cover and 145 essential critical questions to check off in that domain.
The following domains are covered:
Data Engineering, Information engineering, Application development, Australia, Bioinformatics, Business driven, Business process reengineering, Business re-engineering, Clive Finkelstein, Computer-aided software engineering, Computer Science, Data analysis, Database administrator, Database design, Entity-relationship model, Information Architecture, Information Engineering Facility, Information Technology, Information system, Information systems, Integrated Authority File, KnowledgeWare, Rapid application development, Software Engineering, Systems analyst, T.W. Olle, Texas Instruments Software:
Data Engineering Critical Criteria:
Deliberate Data Engineering goals and create Data Engineering explanations for all managers.
– Are there any easy-to-implement alternatives to Data Engineering? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Data Engineering process?
– What are the short and long-term Data Engineering goals?
Information engineering Critical Criteria:
Consolidate Information engineering quality and look at it backwards.
– Think about the kind of project structure that would be appropriate for your Data Engineering project. should it be formal and complex, or can it be less formal and relatively simple?
– What knowledge, skills and characteristics mark a good Data Engineering project manager?
– What are the Key enablers to make this Data Engineering move?
Application development Critical Criteria:
Devise Application development issues and budget the knowledge transfer for any interested in Application development.
– Is the software and application development process based on an industry best practice and is information security included throughout the software development life cycle (sdlc) process?
– What are the key elements of your Data Engineering performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Will applications programmers and systems analysts become nothing more than evaluators of packaged software?
– Which systems play a pivotal role in our organizations continued operations and goal attainment?
– How are we going to realize the benefits of reusability if we keep shrinking the analysis phase?
– Are requirements abstract enough and can they change within limits?
– What is a formalized approach for developing a project schedule?
– What are the advantages and disadvantages of using a rad proces?
– Which sdlc results in the highest degree of user participation?
– What opportunities might a new or enhanced system provide?
– Is there a need to exchange data with other applications?
– What are the primary advantages of the traditional sdlc?
– Is the functionality visible through the uis?
– What is a key aspect of prototyping?
– What are the associated risks?
– What is architected rad?
– Is it applicable?
– When use RAD?
Australia Critical Criteria:
Scan Australia decisions and do something to it.
– What will be the consequences to the business (financial, reputation etc) if Data Engineering does not go ahead or fails to deliver the objectives?
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Data Engineering services/products?
– Do we monitor the Data Engineering decisions made and fine tune them as they evolve?
Bioinformatics Critical Criteria:
Drive Bioinformatics management and explore and align the progress in Bioinformatics.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Data Engineering. How do we gain traction?
– Will Data Engineering deliverables need to be tested and, if so, by whom?
Business driven Critical Criteria:
Shape Business driven strategies and secure Business driven creativity.
– Do several people in different organizational units assist with the Data Engineering process?
– Are there Data Engineering problems defined?
– How to deal with Data Engineering Changes?
Business process reengineering Critical Criteria:
Wrangle Business process reengineering tasks and work towards be a leading Business process reengineering expert.
– In the case of a Data Engineering project, the criteria for the audit derive from implementation objectives. an audit of a Data Engineering project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Data Engineering project is implemented as planned, and is it working?
– When conducting a business process reengineering study, what should we look for when trying to identify business processes to change?
– How can you negotiate Data Engineering successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Does Data Engineering analysis show the relationships among important Data Engineering factors?
Business re-engineering Critical Criteria:
Canvass Business re-engineering tasks and get answers.
– what is the best design framework for Data Engineering organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Is the Data Engineering organization completing tasks effectively and efficiently?
– Who will be responsible for documenting the Data Engineering requirements in detail?
Clive Finkelstein Critical Criteria:
Conceptualize Clive Finkelstein failures and prioritize challenges of Clive Finkelstein.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Data Engineering models, tools and techniques are necessary?
– How can the value of Data Engineering be defined?
Computer-aided software engineering Critical Criteria:
Exchange ideas about Computer-aided software engineering risks and clarify ways to gain access to competitive Computer-aided software engineering services.
– How do senior leaders actions reflect a commitment to the organizations Data Engineering values?
– How much does Data Engineering help?
Computer Science Critical Criteria:
Familiarize yourself with Computer Science governance and differentiate in coordinating Computer Science.
– What business benefits will Data Engineering goals deliver if achieved?
– What are the usability implications of Data Engineering actions?
Data analysis Critical Criteria:
Do a round table on Data analysis strategies and research ways can we become the Data analysis company that would put us out of business.
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– Why is it important to have senior management support for a Data Engineering project?
– Is Supporting Data Engineering documentation required?
– What are some real time data analysis frameworks?
– How can you measure Data Engineering in a systematic way?
Database administrator Critical Criteria:
Systematize Database administrator planning and get answers.
– Think of your Data Engineering project. what are the main functions?
– How will you measure your Data Engineering effectiveness?
Database design Critical Criteria:
Accumulate Database design risks and attract Database design skills.
– Rapid application development (rad) techniques have been around for about two decades now and have been used with varying degrees of success. sometimes rad is required for certain projects. but rad can be bad for database design. why?
– At what point will vulnerability assessments be performed once Data Engineering is put into production (e.g., ongoing Risk Management after implementation)?
– Is the scope of Data Engineering defined?
Entity-relationship model Critical Criteria:
Conceptualize Entity-relationship model engagements and look at it backwards.
– How would one define Data Engineering leadership?
Information Architecture Critical Criteria:
Reconstruct Information Architecture governance and ask questions.
– Have the segments, goals and performance objectives been translated into an actionable and realistic target business and information architecture expressed within business functions, business processes, and information requirements?
– Do you know what your users really want. What sorts of information do they need and expect to be provided as they review search results?
– Has the semantic relationship between information elements been identified based on the information models and classification schemes?
– The level of searching expertise users have: Are they comfortable with Boolean operators, or do they prefer natural language?
– Are we using ontology standards such as OWL and RDF in our information architecture or data management practices?
– Has anyone ever done any user testing to verify if it s a good format/approach?
– Are you constantly questioning: is this content, menu and so on useful?
– Take a look at the site structure listing. What are the major sections?
– Has the time span for the use of this information been analyzed?
– What are the differences in designing a web app vs a website?
– Maybe include pointers to ongoing research in various areas?
– Is this content better suited for a PDF (or other download)?
– Is it worth creating a separate website for mobile browsers?
– Has the time for updating the information been scheduled?
– Identify your audience: who are your main user groups?
– What types of tasks should users be able to perform?
– Is social media a better investment than SEO?
– What Do We Hope to Accomplish?
– Why not the Amazon model ?
– What can you afford?
Information Engineering Facility Critical Criteria:
Pay attention to Information Engineering Facility adoptions and gather Information Engineering Facility models .
– What role does communication play in the success or failure of a Data Engineering project?
– What are the record-keeping requirements of Data Engineering activities?
Information Technology Critical Criteria:
Probe Information Technology issues and diversify by understanding risks and leveraging Information Technology.
– How do your measurements capture actionable Data Engineering information for use in exceeding your customers expectations and securing your customers engagement?
– Do the response plans address damage assessment, site restoration, payroll, Human Resources, information technology, and administrative support?
– Does your company have defined information technology risk performance metrics that are monitored and reported to management on a regular basis?
– If a survey was done with asking organizations; Is there a line between your information technology department and your information security department?
– How does new information technology come to be applied and diffused among firms?
– The difference between data/information and information technology (it)?
– When do you ask for help from Information Technology (IT)?
– Why is Data Engineering important for you now?
– How can we improve Data Engineering?
Information system Critical Criteria:
Dissect Information system planning and use obstacles to break out of ruts.
– Have we developed a continuous monitoring strategy for the information systems (including monitoring of security control effectiveness for system-specific, hybrid, and common controls) that reflects the organizational Risk Management strategy and organizational commitment to protecting critical missions and business functions?
– On what terms should a manager of information systems evolution and maintenance provide service and support to the customers of information systems evolution and maintenance?
– How do you determine the key elements that affect Data Engineering workforce satisfaction? how are these elements determined for different workforce groups and segments?
– Has your organization conducted a cyber risk or vulnerability assessment of its information systems, control systems, and other networked systems?
– Are information security events and weaknesses associated with information systems communicated in a manner to allow timely corrective action to be taken?
– Would an information systems (is) group with more knowledge about a data production process produce better quality data for data consumers?
– What does the customer get from the information systems performance, and on what does that depend, and when?
– What are the principal business applications (i.e. information systems available from staff PC desktops)?
– Why Learn About Security, Privacy, and Ethical Issues in Information Systems and the Internet?
– How secure -well protected against potential risks is the information system ?
– Is unauthorized access to information held in information systems prevented?
– What does integrity ensure in an information system?
– Is authorized user access to information systems ensured?
– How are our information systems developed ?
– Is security an integral part of information systems?
– What is Effective Data Engineering?
Information systems Critical Criteria:
Powwow over Information systems governance and oversee Information systems management by competencies.
– Are information systems and the services of information systems things of value that have suppliers and customers?
– What are information systems, and who are the stakeholders in the information systems game?
– What is our Data Engineering Strategy?
Integrated Authority File Critical Criteria:
Revitalize Integrated Authority File visions and ask questions.
– What tools do you use once you have decided on a Data Engineering strategy and more importantly how do you choose?
– What is the source of the strategies for Data Engineering strengthening and reform?
KnowledgeWare Critical Criteria:
Use past KnowledgeWare governance and find the ideas you already have.
– Is there any existing Data Engineering governance structure?
– How is the value delivered by Data Engineering being measured?
Rapid application development Critical Criteria:
Collaborate on Rapid application development governance and transcribe Rapid application development as tomorrows backbone for success.
– Have we thought of cost, functionality,vendor support, vendor viability, quality of documentation, ease of learning, ease of use, ease of installation, response time, throughput, version?
– Which systems play a pivotal role in an organizations continued operations and goal attainment?
– Schedule feasibility -can the solution be designed and implemented within an acceptable time?
– What type of feasibility is concerned with whether the project can be completed on time?
– Who is responsible for modifying or developing programs to satisfy user requirements?
– What new hardware, software, databases or procedures will improve an existing system?
– Why wait years to develop systems likely to be obsolete upon completion?
– Technical feasibility -is the solution technically practical?
– How do you measure system effectiveness in your organization?
– What primary problems might a new or enhanced system solve?
– Who are the potential users of the new application?
– How do you decide that a system needs rework?
– Can all end user classes be identified?
– Why are sdlcs important?
– When to use dsdm?
Software Engineering Critical Criteria:
Demonstrate Software Engineering issues and tour deciding if Software Engineering progress is made.
– DevOps isnt really a product. Its not something you can buy. DevOps is fundamentally about culture and about the quality of your application. And by quality I mean the specific software engineering term of quality, of different quality attributes. What matters to you?
– Can we answer questions like: Was the software process followed and software engineering standards been properly applied?
– What are the success criteria that will indicate that Data Engineering objectives have been met and the benefits delivered?
– Is open source software development faster, better, and cheaper than software engineering?
– What are all of our Data Engineering domains and what do they do?
– Better, and cheaper than software engineering?
– Is Data Engineering Required?
Systems analyst Critical Criteria:
Weigh in on Systems analyst results and pay attention to the small things.
– Where do ideas that reach policy makers and planners as proposals for Data Engineering strengthening and reform actually originate?
T.W. Olle Critical Criteria:
Unify T.W. Olle strategies and budget for T.W. Olle challenges.
– Is Data Engineering Realistic, or are you setting yourself up for failure?
Texas Instruments Software Critical Criteria:
Rank Texas Instruments Software decisions and attract Texas Instruments Software skills.
– Can we do Data Engineering without complex (expensive) analysis?
– What are the long-term Data Engineering goals?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Data Engineering Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Data Engineering External links:
Data engineering (Journal, magazine, 1984) [WorldCat.org]
IDEAS – International Data Engineering And Science
Information engineering External links:
Information engineering (Book, 1981) [WorldCat.org]
Information engineering (Book, 1992) [WorldCat.org]
Information Engineering – Essential Strategies
Application development External links:
[PDF]Title: Application Development Catalog Description
Application Development | FEMA.gov
Application Development (AppDev) Defined and Explained
Australia External links:
Australia (@Australia) | Twitter
Cialis Generic Australia — RxBuy
Gazelle Holland Festival, Melbourne Australia
Bioinformatics External links:
Wiley – Bioinformatics – Second Edition
BIGP – Bioinformatics, Genomics & Proteomics
Online Courses in Bioinformatics
Business driven External links:
miMeetings – For Business Driven
Business process reengineering External links:
BUSINESS PROCESS REENGINEERING: Essays
Business Process Reengineering – Master Informatix …
[PDF]Business Process Reengineering
Business re-engineering External links:
Using Symbolic Modeling in Business Re-Engineering
Business Re-engineering & Process Improvement – …
Clive Finkelstein External links:
Clive Finkelstein | Employee Benefit News
Computer-aided software engineering External links:
[PDF]Computer-Aided Software Engineering
Computer Science External links:
MyComputerCareer | Computer Science | IT Jobs | …
Computer Science | School of Engineering
Computer Science Department at Princeton University
Data analysis External links:
Regional Data Warehouse/Data Analysis Site
Seven Bridges Genomics – The biomedical data analysis …
AnswerMiner – Data analysis made easy
Database administrator External links:
Database Administrator – Rice University
Database Administrator (DBA) Salary
[PDF]CLASS TITLE: DATABASE ADMINISTRATOR – …
Database design External links:
Custom Internet Database Design-Build Engineering …
[PDF]Title: Database Design – csit.udc.edu
Entity-relationship model External links:
Course Notes for Comp 419 – The Entity-Relationship Model
Information Architecture External links:
Information Architecture Basics | Usability.gov
Information Architecture | The Understanding Group
Information Engineering Facility External links:
IEF (Information Engineering Facility) | Maryrose Mallari
Information Technology External links:
Umail | University Information Technology Services
OHIO: Office of Information Technology |About Email
Information system External links:
[PDF]National Motor Vehicle Title Information System
National Motor Vehicle Title Information System
National Motor Vehicle Title Information System: …
Information systems External links:
TVCCA Information Systems
ISN Corp – Information Systems & Networks Corporation
Mediware Information Systems
Integrated Authority File External links:
MEDLARS indexing: integrated authority file
Integrated Authority File (GND) – Deutsche …
KnowledgeWare External links:
catia Knowledgeware | Formula | Button (Computing)
[PDF]V5 KnowledgeWare Solution – KS Design
KnowledgeWare retries – connection.ebscohost.com
Rapid application development External links:
Best Rapid Application Development (RAD) Software in …
Pega 7 Platform: Rapid Application Development | Pega
RAD (rapid application development) – Gartner IT Glossary
Software Engineering External links:
Codesmith | Software Engineering & Machine Learning
Software Engineering Institute
Systems analyst External links:
Staff and Senior Information Systems Analyst (Series) …
Business Systems Analyst | IllinoisJobLink.com
SENIOR SYSTEMS ANALYST | IllinoisJobLink.com