🎯Michael J Peña - Collected Quotes

"Compression ratios in Parquet often exceed what’s possible with row-based formats because similar data types stored together compress much more efficiently. Columns containing repetitive values (like status codes, country names, or product categories) can achieve compression ratios of 10:1 or better, significantly reducing storage costs and improving query performance. [...] Query performance optimization comes from the ability to skip irrelevant data entirely. Parquet files include metadata that allows query engines to determine whether specific sections of data contain relevant information before reading them." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Data lakes represent a fundamental shift in how organizations store data for analytics. Unlike traditional approaches that required data to be structured and organized before storage, data lakes provide a repository for raw, unprocessed data in its native format. They serve as the foundation for many large-scale analytics architectures, particularly when organizations need to preserve data in its original form. The concept emerged as a response to the increasing variety and volume of valuable data." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Fabric builds on Microsoft’s analytics evolution by unifying previouslyseparate services into an integrated experience that emphasizes simplicityand cohesion. At its foundation lies OneLake, a single data lake that servesas a unified storage layer across all analytical workloads. This approacheliminates the silos that traditionally separated different analytical tools, enabling seamless data sharing and collaboration across roles and teams. The platform brings together multiple workload types under a consistent experience. Data engineers can build and manage pipelines that ingest and transform information. Data scientists can develop and deploy machine learning models. Data analysts can create reports and dashboards. Business users can access self-service analytics. All these personas work within a unified platform that maintains consistent data definitions and governance across activities." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"IoT analytics leverages Stream Analytics to monitor and analyze telemetryfrom connected devices. The service can detect threshold violations, calculate moving averages across measurement windows, identify anomalous patterns, or trigger alerts based on complex event combinations. These capabilities enable scenarios from industrial monitoring to smart building management." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Microsoft Fabric takes a fundamentally different approach to analytics infrastructure by providing a true SaaS experience. Unlike traditional analytics platforms that require significant administration and maintenance, Fabric handles the underlying infrastructure automatically. This approach dramatically reduces operational overhead, allowing organizations to focus on deriving insights rather than managing systems." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Modern data warehouses employ several techniques to deliver performance at scale. Columnar storage organizes data by column rather than row, dramatically improving efficiency for queries that analyze specific attributes across many records. Massively parallel processing (MPP) distributes queries across many computers, enabling analysis of enormous datasets. Intelligent partitioning and indexing strategies optimize data access based on common query patterns." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"OLTP systems are designed for fast, reliable recording of business transactions, while OLAP systems optimize for complex queries across large datasets. Understanding this distinction is crucial for choosing appropriate storage solutions. [...] Query patterns differ dramatically between transactional and analyticalworkloads. Transactional systems typically access small amounts of data in precise locations - finding a specific customer record or updating a particular inventory item. Analytical queries often scan millions or billionsof records, comparing and aggregating information across many dimensions. Stores designed for analytics optimize for these broad, scanning queries rather than precise record access." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Parquet, optimized for Azure Synapse Analytics and Azure Databricks, represents a specialized but increasingly important file format designed specifically for analytical workloads and big data processing. Unlike CSV and JSON, which prioritize readability and interoperability, Parquet optimizes ruthlessly for storage efficiency and query performance in scenarios involving large datasets and analytical processing. The secret to Parquet’s effectiveness lies in its columnar storage approach, which organizes data by columns rather than rows. This organization provides significant advantages for analytical queries that typically operateon subsets of columns across many rows - exactly the pattern common in business intelligence, data warehousing, and analytical reporting scenarios." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Real-time analytics fundamentally changes the relationship between data and decision making. Traditional analytics often involves collecting data over time, storing it in databases or data warehouses, and then periodically analyzing it to identify patterns and insights. This approach, while valuable for historical analysis and long-term planning, introduces significant delays between when events occur and when organizations can react to them. Realtime analytics eliminates this delay, enabling immediate awareness and response to events as they happen." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Stream Analytics processes continuous streams of data through persistent queries that analyze events as they arrive rather than waiting for batch boundaries. These queries apply filtering, aggregation, pattern detection, and joining operations to incoming events, producing analytical results with minimal latency. The service handles the complexity of distributed processing, state management, and fault tolerance, allowing developers to focus on analytical logic rather than infrastructure concerns."(Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Streaming data is inherently unbounded - it has no defined beginning or end but continues flowing indefinitely. [...] These information sources don’t produce cleanly packaged datasets with clear boundaries but generate endless sequences of events. The unbounded nature of streaming data leads to several important characteristics. First, streaming data typically arrives with time sensitivity, where the value of each data point diminishes rapidly after creation. [...] Second, streaming data generally arrives at variable rates rather than in predictable volumes. [...] Third, streaming data often requires stateful processing that maintainscontext across events. [...] Finally, streaming data frequently contains time-based relationships that affect its processing. Events might arrive out of chronological order due tonetwork delays or device characteristics. Analytical windows might need to span time periods to identify patterns." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

"Time sensitivity represents perhaps the most crucial factor. When the value of insights diminishes rapidly after events occur - when minutes or seconds matter - streaming analytics becomes essential. Applications requiring immediate anomaly detection, real-time decision making, or instantaneous personalization benefit from the minimal latency of streaming approaches. Conversely, when analytical value remains relatively constant whether delivered immediately or hours later, batch processing may provide sufficient timeliness while offering advantages in efficiency and completeness." (Michael J Peña, "Azure Data Fundamentals: A Guide to DP-900 Certification and Beyond", 2026)

🧭🏭Business Intelligence: Microsoft Fabric (Part V: One Person Can’t Learn or Do Everything)

Business Intelligence Series

Today’s Explicit Measures webcast [1] considered an article written by Kurt Buhler (The Data Goblins): [Microsoft] "Fabric is a Team Sport: One Person Can’t Learn or Do Everything" [2]. It’s a well-written article that deserves some thought as there are several important points made. I can’t say I agree with the full extent of some statements, even if some disagreements are probably just a matter of semantics.

My main disagreement starts with the title “One Person Can’t Learn or Do Everything”. As clarified in webcast's chat, the author defines “everything" as an umbrella for “all the capabilities and experiences that comprise Fabric including both technical (like Power BI) or non-technical (like adoption data literacy) and everything in between” [1].

For me “everything” is relative and considers a domain's core set of knowledge, while "expertise" (≠ "mastery") refers to the degree to which a person can use the respective knowledge to build back-to-back solutions for a given area. I’d say that it becomes more and more challenging for beginners or average data professionals to cover the core features. Moreover, I’d separate the non-technical skills because then one will also need to consider topics like Data, Project, Information or Knowledge Management.

There are different levels of expertise, and they can vary in depth (specialization) or breadth (covering multiple areas), respectively depend on previous experience (whether one worked with similar technologies). Usually, there’s a minimum of requirements that need to be covered for being considered as expert (e.g. certification, building a solution from beginning to the end, troubleshooting, performance optimization, etc.). It’s also challenging to roughly define when one’s expertise starts (or ends), as there are different perspectives on the topics. 

Conversely, the term expert is in general misused extensively, sometimes even with a mischievous intent. As “expert” is usually considered an external consultant or a person who got certified in an area, even if the person may not be able to build solutions that address a customer’s needs. 

Even data professionals with many years of experience can be overwhelmed by the volume of knowledge, especially when one considers the different experiences available in MF, respectively the volume of new features released monthly. Conversely, expertise can be considered in respect to only one or more MF experiences or for one area within a certain layer. Lot of the knowledge can be transported from other areas – writing SQL and complex database objects, modelling (enterprise) semantic layers, programming in Python, R or Power Query, building data pipelines, managing SQL databases, etc. 

Besides the standard documentation, training sessions, and some reference architectures, Microsoft made available also some labs and other material, which helps discovering the features available, though it doesn’t teach people how to build complete solutions. I find more important than declaring explicitly the role-based audience, the creation of learning paths for the various roles.

During the past 6-7 months I've spent on average 2 days per week learning MF topics. My problem is not the documentation but the lack of maturity of some features, the gaps in functionality, identifying the respective gaps, knowing what and when new features will be made available. The fact that features are made available or changed while learning makes the process more challenging. 

My goal is to be able to provide back-to-back solutions and I believe that’s possible, even if I might not consider all the experiences available. During the past 22 years, at least until MF, I could build complete BI solutions starting from requirements elicitation, data extraction, modeling and processing for data consumption, respectively data consumption for the various purposes. At least this was the journey of a Software Engineer into the world of data. 

References:
[1] Explicit Measures (2024) Power BI tips Ep.328: Microsoft Fabric is a Team Sport (link)
[2] Data Goblins (2024) Fabric is a Team Sport: One Person Can’t Learn or Do Everything (link)

🏭🗒️Microsoft Fabric: Data Governance [Notes]

Disclaimer: This is work in progress intended to consolidate information from various sources for learning purposes. For the latest information please consult the documentation (see the links below)! 

Last updated: 23-May-2024

[Microsoft Fabric] Data Governance

• {definition}set of capabilities that help organizations to manage, protect, monitor, and improve the discoverability of data, so as to meet data governance (and compliance) requirements and regulations [2]
• several built-in governance features are available to manage and control the data within Fabric (MF)  [1]
• {feature} endorsement [aka content endorsement] 
• {definition} formal process performed by admins to endorse MF items
• {benefit} allows admins to designate specific MF items as trusted and approved for use across the organization [1]
• establishes trust in data assets by promoting and certifying specific MF items [1]
• users know which assets they can trust and rely on for accurate information [1]
• endorsed assets are identified with a badge that indicates they have been reviewed and approved [1]
• {scope} applies to all MF items except dashboards [1]
• {benefit} helps admin manage the overall growth of items across your environment [1]
• {feature} promoting [aka content promoting] 
• {definition} formal process performed by contributors or admins to promote content
• promoted content appears with a Promoted badge in the MF portal [1]
• workspace members with the contributor or admin role can promote content within a workspace [1]
• MF admin can promote content across the organization [1]
• {feature} certification [aka content certification]
• {definition} formal process that involves a review of the content by a designated reviewer and managed by the admin [1]
• can be customized to meet organization’s needs [1]
• users can request item certification from an admin [1]
• via Request certification from the More menu [1]
• the certified content appears with a Certified badge in the Fabric portal [1]
• {benefit} allows organizations to label items considered to be quality items [1]
• an organization can certify items to identify them an as authoritative sources for critical information [1]
• ⇐ all Fabric items except Power BI dashboards can be certified [1]
• {benefit} allows to specify certifiers who are experts in the domain [1]
• domain level settings
• enable or disable certification of items that belong to the domain [1]
• provides a URL to documentation that is relevant to certification in the domain [1]
• {feature} tenant (aka Microsoft Fabric tenant, MF tenant)
• a single instance of Fabric for an organization that is aligned with a Microsoft Entra ID
• can contain any number of workspaces
• {feature} workspaces
• {definition} a collection of items that brings together different functionality in a single environment designed for collaboration
• can be assigned to teams or departments based on governance requirements and data boundaries [2]
• are associated with domains [3]
• ⇐ {benefit} allows to group data into business domains
• all the items in the workspace are then associated with the domain, and they receive a domain attribute as part of their metadata [3]
• ⇐ {benefit} enables a better consumption experience [1]
• {benefit} enables better discoverability and governance [2]
• {feature} domains [Notes]
• {definition} a way of logically grouping together data in an organization that is relevant to a particular area or field [1]
• allows to group data by business domains
• ⇒{benefit} allows business domains to manage their data according to their specific regulations, restrictions, and needs [3]
• {feature} subdomains
  • {definition} a way for fine tuning the logical grouping data under a domain [1]
  • ⇐ subdivisions of a domain
• {feature} labeling
• default labeling, label inheritance, and programmatic labeling, 
• {benefit} help achieve maximal sensitivity label coverage across MF [2]
• once labeled, data remains protected even when it's exported out of MF via supported export paths [2]
• [Purview Audit] compliance admins can monitor activities on sensitivity labels
• {feature|preview} folders
• {definition} a way of logically grouping MF items
• {feature|preview} tags
• {benefit} allow managing Fabric items for enhanced compliance, discoverability, and reuse
• {feature} scanner API
• a set of admin REST APIs 
• {benefit} allows to scan MF items for sensitive data [1]
• can be used to scan both structured and unstructured data [1]
• {concept} metadata scanning
• facilitates governance of data by enabling cataloging and reporting on all the metadata of organization's Fabric items [1]
• it needs to be set up by Admin before metadata scanning can be run [1]
• {concept} data lineage
• {definition} 
• {benefit} allows to track the flow of data through Fabric [1]
• {benefit} allows to see where data comes from, how it's transformed, and where it goes [1]
• {benefit} helps understand the data available in Fabric, and how it's being used [1]
• {concept} Fabric item (aka MF item)
• {definition} a set of capabilities within an experience
• form the building blocks of the Fabric platform
• {type} data warehouse
• {type} data pipeline
• {type} semantic model
• {type} reports
• {type} dashboards
• {type} notebook
• {type} lakehouse
• {type} metric set

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Resources:
[1] Microsoft Learn (2023) Administer Microsoft Fabric (link)
[2] Microsoft Learn - Fabric (2024) Governance overview and guidance (link)
[3] Microsoft Learn: Fabric (2023) Fabric domains (link)
[4] Establishing Data Mesh architectural pattern with Domains and OneLake on Microsoft Fabric, by Maheswaran Arunachalam (link) 

Resources:
[R1] Microsoft Learn (2025) Fabric: What's new in Microsoft Fabric? [link]

Acronyms:
API - Application Programming Interface
MF - Microsoft Fabric

#️⃣Software Engineering: Programming (Part II: To get or not Certified?!)

Software Engineering Series

To get or not certified?! That’s a question I asked myself several times along the years, and frankly it doesn’t have an easy answer because there are many aspects that need to be considered: previous education, targeted certification, availability of time, financial resources or learning material, required software, hand-on experience, certification’s costs, duration/frequency, objectives, value (on the market) or requirements, contexts, etc. 

In many occasions when I had most of the conditions met then I didn’t had the time to do it, or I waited to appear the requirements for the new set of certifications, referring mainly to SQL Server 2005 and 2008 versions, or I preferred to continue my “academic” studies, so here I am after almost 10 years of experience in the world of SQL without any certification, but, I would say, with a rich experience covering mainly full-life cycle development of applications, reporting, data quality and data integration, ETL, etc. 

Enough with the talking about myself and get to the subject. I’ve seen recently this topic appearing again in 1-2 professional groups, so I’ll try to approach this topic from a general point of view because most of the characteristics could apply also to database-related certifications like Microsoft MCITP (Microsoft Certified IT Professional) or MCTS (Microsoft Certified Technology Specialist) for SQL Server.

Naturally, in what concerns the certification, the opinions between professionals are split, an often met argument against it is the believe that a certification is just a piece of paper having a limited value without being backed-up by adequate hand-on experience, while the pro-argumentation is that some companies, employers and customers altogether, are valuing a certification, considering it as a personal achievement reflecting not only owners’ commitment to approach and take a certification exam, but also a basic level of knowledge. Both views are entirely correct from their perspective, weighting differently from person to person, community to community or from one domain of expertise to another, and they have positive and negative aspects, many subjective aspects as they are related to people’s perception.

From a global perspective an IT “certification fulfills a great need by providing standardized exams for the most current and important technologies” [3], allowing judging people’s knowledge on the topics encompassed by it[1], being thus a way to quantify knowledge especially related to general tasks. Certifications offer a path to guide the study of a domain [2], are developed around agreed-upon job tasks [3] and consider a basic knowledge base made of vocabulary, definitions, models, standards, methods, methodologies, guidelines or best practices.

Given the fact that a certification covers most of the topics from a given domain, in theory it provides a wide but of superficial depth coverage of the respective domain, in contrast with the hand-on experience, the professional experience accumulated by solving day-to-day tasks, which provides a narrower (task-based) but deeper coverage of the respective domain. Therefore, from my point of view the two are not necessarily complementary but could offer together a wide and deep coverage of the domain, a certification needs somehow to be based on a certain number of years of hand-on experience in order to get more value out of it. 

On the other side, the variety in hand-on experience could offer wider coverage of the domain, though I suppose that could be accomplished fully by had-on experience but in a longer unit of time. These suppositions are fully theoretical because there are many other parameters that need to be considered, for example a person’s capacity of learning by doing vs. theoretical learning (this involves also understanding of concepts), the learning curve and particularities of the technologies, methods or methodologies involved, the forms of training used, etc.

A certification is not meaningless, as several professionals advance (e.g. J. Shore, T. Graves & others), even when considered from employers’ perspective, and the fact that it doesn’t count for some employers or professionals, that’s another story. A certification could be considered eventually useless, though also that’s not fully true. Maybe the certification itself is useless for a third party, though it’s not from the point of view of the learning process, as long the the knowledge accumulated is further used and the certification is not an end in itself.  

A certification is not or it shouldn’t be an end in itself, it should be a continuous learning process in which knowledge is perpetually discovered, integrated and reused. Most probably in order to keep the learning process continuous several certifications, including MCITP, require to be recertified after a number of years.

There are professional certifications that require provable experience in the respective domain before actually being accepted for a certification, it’s the example of PMP (Project Management Professional) and CAPM (Certified Associate in Project Management) certifications from PMI (Project Management Institute) that require a considerable amount of hours of non-overlapping direct or indirect PM experience, and the example is not singular, if I’m not mistaking also the CISP (Certified Information System Security Professional) certification requires a certain number of years of experience. This type of requirement allows in theory to make most of the learning process being facilitated the integration of knowledge with experience.

How useful is a certification for the certified person?! It depends also how much a certification succeeds in covering the knowledge, skills and abilities required by an actual job, how much of the knowledge acquired will be later used. There are people who focus only on taking the exam, nothing more, though I would say that might come with other downsides on the long term. There are even organizations that encourage and even sponsor their employees’ certification either by providing training material, courses, partial or full-expenses, such initiatives being often part of their strategic effort of creating value and a knowledge-based environment, the professional certification being also a form of recognition, being valued in what concerns employees performance, eventually associated also with a form of remuneration.

I think that a certification could be beneficial for a person with relatively small or no professional experience in a certain domain, the certification bridging to a small degree the gap to hand-on experience. It could be interesting to study whether the on-hand experience could be compensated to some degree by attempting to (re)use the learned concepts in self-driven applications or several examples. 

When learning something new I found it useful to try writing a tutorial or a blog post using a well-defined example, though this won’t replace entirely the on-hand experience, the difference between the two being the limited vs. the global scope of handling tasks, in dealing with real-life situations. Most probably it could be also useful to learn about the use of a technique/technology in several contexts, though this equates with lot of research and effort spent in that direction. Does it worth to do that?!

A certification is an opportunity to enter in a “select” circle of professionals, though now it depends also how each vendor or group of certificates takes advantage of this “asset” and what other benefits are derived out of it. For example by publishing domain related content certificates could be kept up-to-date with new features, trends, best practices, etc., the professional network thus created could benefit of the potential such networks offer especially when considering problem solving, the creation, propagation and mapping of knowledge, etc. Of course, such networks could have also side effects, for example the creation of exclusivist networks. I would say that the potential of professional networks is still theoretic, but with the evolution of the Web new possibilities will emerge.

A person taking such a certification arrives in theory to cover most of the important topics related to a given domain, however this doesn’t guarantee that the person is actually capable of applying (successfully) the concepts and techniques in real life scenarios, the many “brain dumps” and other easy ways of taking a certification decreasing certification’s credibility and value. There are domains over-flooded by people with certifications but not having the skills to approach a real project, a company that gives too much credit to a certification could end up stuck with resources that can’t be used, this aspect impacting negatively other professionals too. 

I’m coming back to the idea that a certification is subject of people’s perception and I have to say that the most important opinion in this direction is not necessarily professionals’ opinion activating in the respective domain, but of the people from HR, PM and partially headhunters, because they are the ones who are making the selection, deciding who’s hired and who’s not. Considering that there are few professionals from HR and PM that are coming from the IT domain, there are lot of false and true presumptions when evaluating such candidates, people arriving to come with their own methods of filtering the candidates, and even if such methods are efficient from the result perspective, many good professional could feel kind of “discriminated”.

In theory it’s easier to identify a person who has a certification than to navigate through the huge collection of related projects and tasks, or to search in a collection of CVs for the various possible combinations or significant terms related to a job description. Somebody (sorry, I don’t remember who) was saying that a manager spends on average 20-30 seconds for each CV, now it depends also how eye-catching is a certification in a simple CV scanning. 

From a semantic point of view I would say that a certification is richer in meaning than any type of written experience, though now it depends also on reviewer’s knowledge about the respective certification. Sure is that when choosing between two professionals with similar experience there are high chances for the one having a certification to be hired. In addition, considering that there are hundreds of applicants for the good jobs on the market, I would say that a certification could allow a candidate, between many other criteria, to distinguish himself from the crowd.

Given the explosion of technologies from IT, domain’s dynamics, segmentation and other intrinsic characteristics , the IT certifications are more specialized, more segmented and less standardized, making difficult their evaluation, especially when domains intersect each other or when the vendors emitting the certifications are competing against each other. Compared with other domains, an IT professional needs to be always up-to-date, cover multiple related domains in order to do his work efficiently, for example in order to provide a full-life cycle solution a developer would have to be kind of expert in Software Engineering, UI and database programming, security, testing, etc. The high segmentation in IT could be seen also in the denominations for the various roles, lot of confusion deriving from this, especially when matching the job descriptions with the roles.

Must be considered also the bottom line: in IT as also in other domains, the knowledge and experience is relative because it depends also on person’s skills and ability of assimilating, using, reusing (creatively) the knowledge given in a domain; a person could in theory accumulate in one year same experience as others in 2 or more years, same as a person who got certified could in theory handle day-to-day tasks without any difficulty, same as in theory a student with no professional experience could handle programming tasks like a professional with several years of experience. 

At least in my country, there are many domains in University that provide also IT-related curricula within non-IT domains (e.g. Mathematics, Economics, Engineering), a number of programming courses being thought also in high school or even lower grades, the theory learned and the small projects facilitating theoretically the certification for a programming language (e.g. C#, Java or C++) or of directly handing day-to-day tasks. It’s true that in school is insisted more on the syntax, basic features and algorithmic nature of programming, but this doesn’t diminish the value of this type of learning when done adequately. Such educational experience is not considered as professional experience at all, even if it provides a considerable advantage when approaching a certification or a job.

It must be highlighted that taking a certification comes with no guarantees for getting a job or being successful in your carrier/profession. You have to ask yourself honestly what you want to achieve with a certification, how you’ll use the learning process in order to get most of it. You actually have to enjoy the road to the final destination rather than dreaming about the potential success brought by such a certification. It could take actually more time until you’ll recover your investment or you’ll see that the actual invested time worth, and, as always some risks need to be assumed. Consider the positive and negative aspects altogether and decide by yourself if it makes sense to go for a certification.

There is actually a third choice – continuing the academic studies, for example pursuing a bachelor, masters or why not, a doctoral degree. The approach of a such a degree imposes similar questions as in the case of a certification, though academic degrees are in theory better accepted by the society even if they come with no guarantees too, require more effort and financial resources.

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References:
[1] K. Forsberg, H. Mooz, H. Cotterman. (2005). Visualizing Project Management: Models and Frameworks for Mastering Complex Systems. John Wiley & Sons. ISBN: 0-978-0-471-64848-2.
[2] D. Gibson (2008). MCITP SQL Server 2005 Database Developer All-In-One Exam Guide. McGraw-Hill. ISBN: 978-0071546690.
[3]  L.A. Snyder, D.E. Rupp. G.C. Thornton (2006). Personnel Selection of Information Technology Workers: The People, The Jobs, and Issues for Human Resources Management. Research in Personnel and Human Resources Management, Vol. 25, Martocchio J.J. (Ed.). JAI Press. ISBN: 978-0762313273.