Tag: Pearl Zhu

Fresh Links Sundae – December 7, 2014 Edition

Fresh Links Sundae encapsulates information I have come across during the past week. Often they are from the people whose work I admire or resonate with me. I hope you will find these ideas thought-provoking at the minimum. Even better, I hope these ideas will, over time, help my fellow IT pros make better decisions, be awesome, and kick ass!

Having a functional architecture is a key to deriving IT values for any organization, and architecture calls for sound design principles. Bob Lewis recommends at least five areas to consider when putting together the design principles for your architecture. Ben Franklin, turkeys, and design principles (IS Survivor Publishing)

As we jump from one data analytics problem to another, we often need to get up to speed on a new dataset quickly. A classical and under-utilized approach for becoming familiar with the new data problem is Exploratory Data Analysis (EDA). Jason Brownlee explains the EDA techniques and tactics that you can use. Understand Your Problem and Get Better Results Using Exploratory Data Analysis (Machine Learning Mastery)

Verified inventory is one of the several key elements of IT assets management success. Martin Thompson shares techniques he has used in the past to verify hardware inventory. Verifying Asset Accuracy (The ITAM Review)

As business analysts, there will always be value in getting more done well and in less time. Laura Brandenburg talks about some of the most common time wasters she sees in business analysis. 5 Business Analyst Time-Wasters (Bridging the Gap)

For many organizations, an ITSM initiative often represents a major change, and Organizational Change Management (OCM) is the centerpiece to success. Mike DePolis discusses some of the most important aspects and actions to consider for an OCM effort in your organization. Project success with Organizational Change Management (OCR) (The ITSM Review)

Many organizations still perceive data quality projects to be a technical endeavor, but data quality requires an on-going, consistent change management effort. Such changes can often result in fear and resistance. Dylan Jones discusses ways to combat the fear and resistance to changes. Data quality mastery depends on change management essentials (The Data Roundtable)

Data or information Management within an organization can be at risk when data are in bad shape. Strong governance practices and stewardship can minimize risks and improve productivity. Pearl Zhu outlines the signals we should pay attention to when handling data governance within your organization. How to Capture the Signals of Data Governance Issues (Future of CIO)

Marshall Goldsmith believes how you define yourself will impact how successful you are at your job and even how happy you will be in life. He outlines four sources from which we can define our identity and encourages us to think about the considerations that go into how we define ourselves. Why You Should Get a Handle on Your Identity (Marshall Goldsmith Personal Blog)

Fresh Links Sundae – November 23, 2014 Edition

A baseline is necessary to gauge and to validate the results produced by machine learning algorithms. Jason Brownlee describes why we create a baseline prediction result and how to create a baseline in general and for specific problem types. How To Get Baseline Results And Why They Matter (Machine Learning Mastery)

From KDNuggets, Burtch Works details the top 9 data science skills that potential data scientists must have to be competitive in this growing marketplace from the perspective of a recruiter. 9 Must-Have Skills You Need to Become a Data Scientist (KDNuggets)

Accurate asset tracking and management can be an enormous task for any IT organization. In a four-part series, Marcel Shaw describes a three-tiered approach to assets management. IT Asset Management, a three-tiered approach IT Asset Management, a Three-Tiered Approach (Part 2 of 4) IT Asset Management, a Three Tiered Approach (Part 3 of 4) IT Asset Management, a Three-Tiered Approach (Part 4 of 4) (LANDESK Blog)

Bob Lewis points out many enterprise technical architecture management (ETAM) efforts suffer from the pitfall where it cannot keep up with the changes within the organization. He further suggests that perhaps an agile approach to ETAM will be necessary. Technical architecture’s irreducible core (IS Survivor Publishing)

A well-known problem troubleshooting and root-cause analysis technique has been the Five Why’s. John Allspaw argues that, for maximum learning effectiveness, we also need to ask more questions about the How’s. The infinite hows (O’Reilly Radar)

Every organization needs to assess its information security readiness from time to time and implement improvements or remediation when necessary. Chris Sell walks through the four steps that are critical for every information security gap analysis. How To Conduct An Information Security Gap Analysis (SunGard)

Although analytics projects are often at the top agenda for organizations these days, many of those organizations are still struggling to identify the business problems where analytics could generate measurable ROI. Pearl Zhu suggests the ways organizations can use to improve their analytics ROI. How can Organizations Improve their Analytics ROI (Future of CIO)

For most of us, it is easier to see our behavioral challenges in others than to see them in ourselves. From his own experience, Marshall Goldsmith discusses two important life lessons he had learned about addressing those challenges from within. 2 Life-Changing Lessons No One Ever Taught You (Marshall Goldsmith Personal Blog)

Fresh Links Sundae – November 2, 2014 Edition

Thomas Redman believes that managers should rarely take an important analysis at face value. He explains how data can be interpreted to tell one story but still fail to present the whole picture. When It Comes to Data, Skepticism Matters (Harvard Business Review)

Like all technology implementation efforts, cost benefits analysis should be part of a NoSQL implementation. William Vorhie explains what the two categories of benefit in NoSQL are and how to quantify them. Quantifying the Value of a NoSQL Project (Data Science Central)

Most of us think of taking meeting notes as merely a mundane transcription exercise. Bob Lewis would argue that taking and publishing the meeting notes is one of the most important jobs in a meeting. Notes about notes (IS Survivor Publishing)

Glen Alleman would advocate that, in order to make good decisions, we require good estimates. He explains five decision-making processes and how to incorporate sound estimating effort into those processes. Decision Making Without Estimates? (Herding Cats)

Understand the algorithm is a critical element of leveraging machine learning techniques effectively. Jason Brownlee outlines five ways to study and learn about machine learning algorithms. How to Study Machine Learning Algorithms (Machine Learning Mastery)

Many organizations do not have an organized approach to handling major IT incidents, and, as a result, they compromise their abilities to capture valuable lessons. Ryan Ogilvie discusses the four stages of a major incident handling and what challenges we need to overcome. Not Doing Proper Post Incident Reviews Could Haunt You (Service Management Journey)

Many organizations spend a great deal of effort on IT benchmarking but often get back the results that have little impact. Pearl Zhu discusses how to do benchmarking effectively in order to get the most impactful results from the effort. Is IT Benchmarking valuable or a Waste? (Future of CIO)

With the current and future landscape of tools, technologies, and processes, the IT environment has been changing in a fast and dramatic pace. Chris Riley discusses the challenges IT and Operations will face now and into 2015 and how to address those challenges. 6 Challenges Facing DevOps and Operations Teams in 2015 (logentries)

Fresh Links Sundae – September 28, 2014 Edition

In a 9-part series, William Vorhies discusses the important considerations that can help you determine which NoSQL technology is appropriate for your project. I featured parts one through five last week. We feature parts six through nine here to wrap things up. Lesson 6: Document Oriented Databases Lesson 7: Column Oriented Databases (aka Big Table or Wide Column) Lesson 8: Graph Databases Lesson 9: Making Your Selection – Final Considerations (Data Science Central)

Today’s business leaders need to understand enough about data analytics in order to begin to appreciate the opportunities possible by leveraging data. Alex Jones discusses a variety of different data analytics approaches along with their advantages and limitations from a business leader’s perspective. Data Analytics for Business Leaders Explained and Advanced Data Analytics for Business Leaders Explained (KDnuggets)

Many organizations believe they must hire data scientists from outside who will come with both broad and extensive background in order to succeed. Michael Schrage recommends a different approach in which organizations grow their data science talents from within the enterprise. Stop Searching for That Elusive Data Scientist (Harvard Business Review)

Analytics project is one of the top priorities for many organizations these days. IT is in a unique position to play a pivotal role in managing the full information life cycle. Pearl Zhu explains how CIOs can take on the adventure of analytics projects and deliver the business value from deploying them. CIO as Chief Analytics Officer (Future of CIO)

Data migrations are rarely an attractive of projects to sponsor. On occasions, the migration activities can be seen a difficult, bitter pill to take in and digest. Dylan Jones outlines the areas where the sponsors for data migration projects need to have considerable input and oversight. Are you a data migration sponsor? A reminder of your responsibilities. (The Data Roundtable)

Spreading the good news of business intelligence (BI) technology requires marketing, but good news alone will not be enough to move people to action. Max Russell explains how IT can leverage good marketing practices to improve its effectiveness in implementing and supporting BI in the enterprise. Marketing IT In-House: Good News Is Not Enough (TDWI)

Cloud computing has changed how IT operate and interact with its business constituents. Pierre Moncassin discusses how IT needs to transform itself towards providing services in a software-defined data center environment. A New Angle on the Classic Challenge of Retained IT (VMware CloudOps)

Decision making is the most prominent and critical element of a leader’s responsibility. When it comes to effective decision making, Eric McNulty outlines the four key tests of any critical decision. The Four Rs of High-Stakes Decision Making (Strategy+Business)

Fresh Links Sundae – September 21, 2014 Edition

In a 9-part series, William Vorhies discusses the important considerations that can help you determine which NoSQL technology is appropriate for your project. Parts one through five are listed here to start things out. 9 Lessons: Picking the Right NoSQL Tools Lesson 2: NoSQL Databases are Good for Everything – Except Maybe this One Thing Lesson 3: Open Source, Distribution, or Suite Lesson 4: Features Common to (Most) NoSQL/NewSQL Databases Lesson 5: Key Value Stores (AKA ‘Tuple’ Stores) (Data Science Central)

Cloud computing is here to stay, and many organizations have begun implementing their private clouds. Thomas Bittman talks about ten reasons why most organization fails to get the most out of their private cloud efforts. Why Are Private Clouds Failing? (Gartner Blogs)

Many organizations hire for skills and aptitude, but are there other elements that play an even more critical role in the organization’s success? Stephen Mann suggests that the attitude of the IT staff can go a long way in shaping and promoting their organization’s chance to succeed. Working In IT: Does Your Attitude Determine You… (ServiceNow)

Effective software asset management (SAM) is a crucial component of any IT operation, but the scope of SAM needs to be well-defined and precise, or it could become unmanageable quickly. Brent Jarnell talks about what to consider when designing your SAM practice. Setting the scope in SAM design (The ITAM Review)

When operating a complex system, it is often difficult to grasp the potential connections between many data sources which are part of the system. Rita McGrath explains how predictive analytics can now help organizations gain more insights into their business by bringing more disparate data stores together. To Make Better Decisions, Combine Datasets (Harvard Business Review)

When adopting a non-waterfall project management practice, some organizations had to face the decision of whether to adopt Scrum or Kanban. Simon Morris discusses the similarities and differences of those two approaches and how to be successful with either. Scrum vs. Kanban (The ITSM Review)

Many IT organizations have a significant portion of their budget goes into maintaining operations and application portfolio. Pearl Zhu gives suggestions on managing a balanced IT portfolio and how to run IT more effectively. IT Portfolio Management (Future of CIO)

Conducting proof-of-concept (POC) projects to test out a new idea is a popular approach, but many POC efforts fall into the traps of wasted valuable time and resources. Bob Lewis talks about how to avoid those traps when conducting POCs. How to prove a proof of concept (IS Survivor Publishing)