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9 Project Ideas for Your Data Analytics Portfolio

Finding the right data analyst portfolio projects can be tricky, especially when you’re new to the field. You might also think that your data projects need to be especially complex or showy, but that’s not the case. The most important thing is to demonstrate your skills, ideally using a dataset that interests you. And the good news? Data is everywhere—you just need to know where to find it and what to do with it.

A good option for getting experience in all domains is to take a  data analytics program  or course. We offer  a top-rated one here at CareerFoundry.

In this article, I’ll highlight the key elements that your data analytics portfolio should demonstrate. I’ll then share nine project ideas that will help you build your portfolio from scratch, focusing on three key areas: Data scraping , exploratory analysis , and data visualization .

Table of contents

• What data analytics projects should you include in your portfolio?
• Data scraping project ideas
• Exploratory data analysis project ideas
• Data visualization project ideas
• What’s next?

Ready to get inspired? Let’s go!

1. What data analytics projects should you include in your portfolio?

Data analytics is all about finding insights that inform decision-making. But that’s just the end goal.

As any experienced analyst will tell you, the insights we see as consumers are the result of a great deal of work. In fact, about 80% of all data analytics tasks involve preparing data for analysis . This makes sense when you think about it—after all, our insights are only as good as the quality of our data.

Yes, your portfolio needs to show that you can carry out different types of data analysis . But it also needs to show that you can collect data, clean it, and report your findings in a clear, visual manner. As your skills improve, your portfolio will grow in complexity. As a beginner though, you’ll need to show that you can:

• Scrape the web for data
• Carry out exploratory analyses
• Clean untidy datasets
• Communicate your results using visualizations

If you’re inexperienced, it can help to present each item as a mini-data analyst portfolio project of its own . This makes life easier since you can learn the individual skills in a controlled way.

With that in mind, I’ll keep it nice and simple with some basic ideas, and a few tools you might want to explore to help you along the way.

2. Data scraping project ideas for your portfolio

What is data scraping.

Data scraping is the first step in any data analytics project. It involves pulling data (usually from the web) and compiling it into a usable format. While there’s no shortage of great repositories available online, scraping and cleaning data yourself is a great way to show off your skills.

The process of web scraping can be automated using tools like Parsehub , ScraperAPI , or Octoparse (for non-coders) or by using libraries like Beautiful Soup or Scrapy (for developers). Whichever tool you use, the important thing is to show that you understand how it works and can apply it effectively.

Before scraping a website, be sure that you have permission to do so. If you’re not certain, you can always search for a dataset on a repository site like  Kaggle . If it exists there, it’s a good bet you can go straight to the source and scrape it yourself. Bear in mind though—data scraping can be challenging if you’re mining complex, dynamic websites. We recommend starting with something easy—a mostly-static site. Here are some ideas to get you started.

Data scraping portfolio project ideas

The internet movie database.

A good beginner’s project is to extract data from IMDb. You can collect details about popular TV shows, movie reviews and trivia, the heights and weights of various actors, and so on. This kind of information on IMDb is stored in a consistent format across all its pages, making the task a lot easier. There’s also a lot of potential here for further analysis.

Job portals

Many beginners like scraping data from job portals since they often contain standard data types. You can also find lots of online tutorials explaining how to proceed.

To keep it interesting, why not focus on your local area? Collect job titles, companies, salaries, locations, required skills, and so on. This offers great potential for later visualization, such as graphing skillsets against salaries.

E-commerce sites

Another popular one is to scrape product and pricing data from e-commerce sites. For instance, extract product information about Bluetooth speakers on Amazon, or collect reviews and prices on various tablets and laptops.

Once again, this is relatively straightforward to do, and it’s scalable . This means you can start with a product that has a small number of reviews, and then upscale once you’re comfortable using the algorithms.

For something a bit less conventional, another option is to scrape a site like Reddit. You could search for particular keywords, upvotes, user data, and more. Reddit is a very static website, making the task nice and straightforward. You could even scrape Reddit for useful data analytics advice .

Later, you can carry out interesting exploratory analyses, for instance, to see if there are any correlations between popular posts and particular keywords. Which brings me to our next section…

3. Exploratory data analysis project ideas

What is exploratory data analysis.

The next step in any data analyst’s skillset is the ability to carry out an exploratory data analysis (EDA). An EDA looks at the structure of data, allowing you to determine their patterns and characteristics. They also help you to it up. You can extract important variables, detect outliers and anomalies, and generally test your underlying assumptions.

While this process is one of the most time-consuming tasks for a data analyst, it can also be one of the most rewarding. Later modeling focuses on generating answers to specific questions. An EDA, meanwhile, helps you do one of the most exciting bits—generating those questions in the first place.

Languages like R and Python are often used to carry out these tasks. They have many pre-existing algorithms that you can use to carry out the work for you . The real skill lies in presenting your project and its results. How you decide to do this is up to you, but one popular method is to use an interactive documentation tool like Jupyter Notebook . This lets you capture elements of code, along with explanatory text and visualizations, all in one place. Here are some ideas for your portfolio.

Exploratory data analysis portfolio project ideas

Global suicide rates.

This global suicide rates dataset covers suicide rates in various countries, with additional data including year, gender, age, population, GDP, and more. When carrying out your EDA, ask yourself: What patterns can you see? Are suicides rates climbing or falling in various countries? What variables (such as gender or age) can you find that might correlate to suicide rates?

World Happiness Report

On the other end of the scale, the World Happiness Report tracks six factors to measure happiness across the world’s citizens: life expectancy, economics, social support, absence of corruption, freedom, and generosity. So, which country is the happiest? Which continent? Which factor appears to have the greatest (or smallest) impact on a nation’s happiness? Overall, is happiness increasing or decreasing? Access the happiness data over on Kaggle .

Create your own!

Aside from the two ideas above, you could also use your own datasets . After all, if you’ve already scraped your own data, why not use them? For instance, if you scraped a job portal, which locations or regions offer the best-paid jobs? Which offer the least well-paid ones? Why might that be? Equally, with e-commerce data, you could look at which prices and products offer the best value for money.

Ultimately, whichever dataset you’re using, it should grab your attention. If the information is too complex or don’t interest you, you’re likely to run out of steam before you get very far. Keep in mind what further probing you can do to spot interesting trends or patterns, and to extract the insights you need.

We’ve compiled a list of ten great places to find free datasets for your next project .

4. Data visualization project ideas

What is data visualization.

Scraping, tidying, and analyzing data is one thing. Communicating your findings is another. Our brains don’t like looking at numbers and figures, but they love visuals. This is where the ability to create effective data visualizations comes in.

Good visualizations—whether static or interactive—make a great addition to any data analytics portfolio. Showing that you can create visualizations that are both effective and visually appealing will go a long way towards impressing a potential employer.

Some free visualization tools include Google Charts , Canva Graph Maker , and Tableau Public . Meanwhile, if you want to show off your coding abilities, use a Python library such as Seaborn , or flex your R skills with Shiny . Needless to say, there are many tools available to help you. The one you choose depends on what you’re looking to achieve. Here’s a bit of inspiration…

Data visualization portfolio project ideas

Topical subject matter looks great on any portfolio, and the pandemic is nothing if not topical! What’s more, sites like Kaggle already have thousands of Covid-19 datasets available .

How can you represent the data? Could you use a global heatmap to show where cases have spiked, versus where there are very few? Perhaps you could create two overlapping bar charts to show known infections versus predicted infections. Here’s a handy tutorial to help you visualize Covid-19 data using R, Shiny, and Plotly .

Most followed on Instagram

Whether you’re interested in social media, or celebrity and brand culture, this dataset of the most-followed people on Instagram has great potential for visualization. You could create an interactive bar chart that tracks changes in the most followed accounts over time. Or you could explore whether brand or celebrity accounts are more effective at influencer marketing.

Otherwise, why not find another social media dataset to create a visualization? For instance, data scientist Greg Rafferty’s map of the USA nicely highlights the geographical source of trending topics on Instagram.

Travel data

Another topic that lends itself well to visualization is transport data. There’s a great project by Chen Chen on github , using Python to visualize the top tourist destinations worldwide, and the correlation between inbound/outbound tourists with gross domestic product (GDP).

5. What’s next?

In this post, we’ve explored which skills every beginner needs to demonstrate through their data analytics portfolio project ideas. Regardless of the dataset you’re using, you should be able to demonstrate the following abilities:

• Web scraping —using tools like Parsehub, Beautiful Soup, or Scrapy to extract data from websites (remember: static ones are easier!)
• Exploratory data analysis and data cleaning —manipulating data with tools like R and Python, before drawing some initial insights.
• Data visualization —utilizing tools like Tableau, Shiny, or Plotly to create crisp, compelling dashboards, and visualizations.

Once you’ve mastered the basics, you can start getting more ambitious with your data analytics projects. For example, why not introduce some machine learning projects , like sentiment analysis or predictive analysis? The key thing is to start simple and to remember that a good portfolio needn’t be flashy, just competent.

To further develop your skills, there are loads of online courses designed to set you on the right track. To start with, why not try our free, five-day data analytics short course ?

And, if you’d like to learn more about becoming a data analyst and building your portfolio, check out the following:

• How to build a data analytics portfolio 
• The best data analytics certification programs on the market right now
• These are the most common data analytics interview questions

Case Studies in Portfolio Management

• Background information: The case study begins by providing context and relevant details about the portfolio, its goals, and the market environment.
• Problem statement: The specific issue or challenge faced by the portfolio manager is clearly defined.
• Data and analysis: The case study presents relevant data, such as historical performance, risk metrics, and economic indicators. It may also include analyses and insights from the portfolio manager.
• Decision-making process: The case study describes the thought process and methodology used by the portfolio manager to evaluate options and make decisions.
• Outcome and reflection: The case study concludes by discussing the results of the portfolio manager's actions and any lessons learned.
• Read the case study carefully and identify the key issues and objectives.
• Analyze the provided data and information to gain insights into the portfolio's performance and risk characteristics.
• Apply relevant portfolio management concepts and theories to the specific situation.
• Develop a clear and well-reasoned solution or recommendation based on your analysis.
• Support your answer with evidence from the case study and your understanding of portfolio management principles.
• Read the case study thoroughly and highlight important information.
• Identify the main problem or decision point that needs to be addressed.
• Break down the problem into smaller components and analyze each one separately.
• Apply relevant formulas, models, and frameworks to support your analysis.
• Be specific and provide concrete examples from the case study to back up your arguments.
• Manage your time effectively and allocate sufficient time to read, analyze, and answer each question.
• Write clear and concise answers, focusing on the most important points.

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Case Studies in Portfolio Management practice test

Time: 5 minutes    Questions: 5

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How I completed My BellaBeat Case Study (Portfolio Project)

Sameerah_writes

In August 2023, in order to complete the Data Analytics Google Certification Course, had to partake in a Case study where I utilized R from the cleaning up to visualization.

If you need to complete the analysis, you can see my process and technique below, a link to my Kaggle, and the report will be at the end.

Introduction

Founded in 2013, Bellabeat is a successful small high-tech company that manufactures health-focused smart products.

The Co-Founder wants to focus on one Bellabeat product and analyze smart device usage data in order to gain insight into how people are already using their smart devices.

The chosen device for this analysis is the Bellabeat App which provides users with health data related to their activity, sleep, stress, menstrual cycle, and mindfulness habits.

Business Task : Analyze smart device usage data in order to gain insight into how consumers use non-Bellabeat smart devices.

Problem : How can Bellabeat incorporate insights from smart device usage into their products?

Data Sources Used

The dataset for analysis was downloaded from the Fitbit Fitness Tracker Data uploaded on Kaggle via Public Domain. This dataset was made available through Mobius on Kaggle.

The data sets included 18 sheets from Daily to Hourly to Minutes with a focus on the daily activity, calories, intensities, steps, heart rate, METs, sleep, and weight log info on personal fitness trackers data collected from thirty Fitbit users between 03/12/2016–05/12/2016.

This data is deemed credible as it operates under a public domain with data made available by Mobius, a Data Scientist at Healthcare Melbourne, Victoria, Australia.

The data was checked with pivot tables in Excel and the time for the Daily Activity, Daily Sleep, and Hourly Step data sets were manipulated into “week_day” to assist with the analysis. With 1 being Sunday and 7 being Saturday

Loading the library for datasets

The following packages for the cleaning and analysis are loaded in the code chunk below;

Importing the datasets for the analysis

The following data sets were the focus of the analysis and will be imported below;

• dailyActivity_merged.csv
• sleepDay_merged.csv
• hourlySteps_merged.csv

Assigning versions to the datasets.

The datasets will be assigned versions in case of an error and I have to refer to original data. The imported datasets will be renamed and the column names will be cleaned using the (clean_names) function to make it easier for analysis.

Inspecting the datasets

The data sets will be checked with the “head”, “str”, and “colnames” functions.

Cleaning the date-time format

The date format in the dataset is in a date-time format and will be converted to date format (“m”/”d”/”y”) to make it more consistent.

Checking for distinct id numbers

The number of id(s) has to be checked.

The dataset has a total of 33 people and it is correlating with the sample data that we downloaded. We can proceed to analysis.

Summary Statistics

The following columns were selected from each imported data sets and a summary of each data sets were carried out.

• Activity_data_v1: total_steps, total_distance, calories, sedentary_minutes, very_active_minutes, lightly_active_minutes, moderately_active_distance
• Sleep_data_v1: total_sleep_records, total_minutes_asleep, total_time_in_bed
• Step_data_v1: step_total

The average steps taken per day is 7638 and the average distance walked in a day is 5.490 kilometers. The recommended steps by the Centers for Disease Control and Prevention (CDC) to be taken per day is approximately 10,000 steps and the distance recommended per day is 8 kilometers per day. Users need to improve.

The average calories burned per day is 2304 and the recommended daily calorie burning is 2,000 calories a day for women and 2,500 for men, which means users are right on track.

The users spend 991.2 minutes seated which equates to 16 hours a day, 16 hours of sitting a day is highly risky and users should try to reduce it to a recommended total of 4 hours per day.

Most of the users are lightly active users.

The average minute spent asleep is 419.5 minutes which equates to about 6.9 hours a day and 458.6 minutes in bed which equates to 7.64 hours a day. This sleep pattern needs to be increased to about 7 and above hours which is recommended for adults.

The users also spend 1 day sleeping 6.9 hours a day, which they need to improve to improve their health.

Merging data for Visualization

We will have to merge the data (JOIN) by the “id” and “date” and “week_day” columns to have one central table for the visualization.

First off, the sleep_day column from Sleep_data_v1 will be renamed into (date).

Visualizing the charts.

Chart 1: steps vs. calories.

The point chart shows a positive relationship between Total Steps and Calories which shows that the more users walk, the more calories they burn.

Chart 2: Total minutes asleep vs. Total minutes in bed.

The above point chart shows that the more users spend in bed, the more time they spend asleep.

Chart 3: Sedentary Minutes vs. Total Minutes Asleep

The point chart shows a negative relationship which means that as sedentary minutes decrease, the total minutes asleep increase so users need to decrease it.

Chart 4: Weekdays.

This bar chart shows that the most active weekday is Wednesday.

Recommendations for Bellabeat

After analyzing the data sets and performing a summary analysis on how consumers use non-Bellabeat smart devices, the following are the concluding recommendations for BellaBeat to incorporate into their Bellabeat app and marketing strategy.

• The Bellabeat app should recommend the total recommended steps to be walked in a day so users can make sure to walk these steps and also promote their enthusiasm by coming up with a weekly scoreboard that users can compete for.
• The Bellabeat app can be used by users to improve their sleep patterns by analyzing their sleep patterns and suggesting suitable times for them to sleep so they can get the most sleep recommended.
• The Bellabeat app can help users reduce their sedentary time by suggesting activities to be done instead and also providing articles on the health benefits of having shorter sedentary time through pop notifications.
• Bellabeat app can suggest activities to the users on the days when they are least active and also send users articles on the benefits of being active.

These are my recommendations for Bellabeat to incorporate which answers the business question.

You can my Kaggle here and the report for the analysis below:

Written by Sameerah_writes

Tech Content Writer

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Apple Inc.: Product Portfolio Analysis

2011, Journal of the International Academy for Case Studies

This case assesses a company’s product line mix relative to two marketing environmental factors and explores four product line growth strategies using a product portfolio analysis approach. The case provides a history of the Apple Computer Company and its key product lines. An approach to analyzing a company’s product portfolio is reviewed and applied to Apple’s product lines. The case shows how each Apple product line fits within the portfolio analysis tool and will be asked questions relative to possible strategies for Apple’s product portfolio. The case illustrates one approach to making decisions about a company’s line of products. The case also stimulates critical thinking in regards to the future direction of a company’s product portfolio.

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The aim of this article is to provide reader with a comprehensive insight on the theories, empirical findings and models of Product Portfolio Management (PPM) during new product development. This article will allow for an in-depth theoretical approach on PPM and demonstrate to managers the importance of adopting PPM as business strategy during decision making. The objective of this paper is to present a literature review of models, theories, approaches and findings on the relationship between Product Portfolio Management and new product development. Relevant statistical trends, historical developments, published opinion of major writers in this field will be presented to provide concrete evidence of the problem being discussed.

IFIP Advances in Information and Communication Technology

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This work aims to analyze the relationship of the diversification of products with the brand positioning and his time with business growth, on the assumption that the strategy is applicable in the diversification of products for brand positioning and generate a considerable business growth, In this analysis used the qualitative method on the basis of a case study of an efficient company that complies with the requirements to be applied the theory of resources and capacities because of their activity and business history. In conclusion, the case study we provides relevant data that allows you to identify the correlation between the diversification of products and brand positioning, and that these in turn are important factors for business growth due to the needs that arise when diversifying the production, such as broadening the current facilities or opening new plants for the supply of production.

Journal of Retailing and Consumer Services

Juliene Leoni , Manoel Henrique Salgado

Because they define not only projects for new products, but also revisions, updates, and decisions to discontinue products that are produced and sold, the management methods applied to the product portfolio are important elements for a good performance in the new product development. This paper aims to show the main methods large and medium-sized companies in the electronics, optical, and computer science sectors adopt for decision making involving the product portfolio. For such, a survey was conducted on a sample of 40 companies that operate in Brazil. Many of the firms follow an informal standard for such decision making. Among the formal methods used, the most present in the sectors surveyed were financial, market research, and mapping.

Hemerson M Ramos

In December 1980, Apple Inc. went public presenting an initial price share of $22. Within minutes, the company’s market price was worth $1.78bn, marking a financial trend that culminated in Apple’s actual worth value of $1 trillion (Neate, 2015). The company’s core values, base for the formulation of Apple’s strategies, are undoubtedly responsible for its current success in the high-tech market, being perceived by stakeholders worldwide as a disruptive company in terms of innovation, technology and design (Gustin, 2015). Gendron (2012) notes that in order to evaluate the success of a company, it becomes imperative the utilisation of business analysis tools. Therefore, this report will discuss how Apple’s strategies have been used to build and sustain competitive advantage, allowing the company to become a benchmark to all players in the technological market. Moreover, while not offering recommendations, this paper intends not only to highlight Apple’s strategies for success, but also to present some of the issues faced by the company in the adoption of certain strategic decisions. Finally, the methodology employed in this investigation consists in the utilisation of theoretical tools such as SWOT, Porter’s Five Forces, Value Chain and Three Horizons. An evaluation of the usefulness of these strategic tools is presented, proposing a discussion in relation to the effectiveness of frameworks created in an ‘analogic’ world in the current ever-changing reality we live in.

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Diversity Technology and Innovation For Operational Competitiveness Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management

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Considering the number of new product introductions and available product varieties today, the practice of product proliferation is visibly evident in many diverse industries. Given its prevalence in practice, understanding the determinants and implications of firm proliferation strategies clearly has important managerial relevance. Previous theoretical research has identified three primary effects of a proliferation strategy: (1) a broad product line can increase the overall demand faced by the firm, (2) a broad product line can affect supply by increasing costs, and (3) broad product lines can have strategic consequences (e.g., long product lines can deter entry, thereby allowing an incumbent firm to raise prices). However, despite the theoretical interest in this common business practice, there has been very little empirical research on this topic. Moreover, no empirical study has simultaneously considered all three of the possible effects associated with a proliferation strategy...

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How Motilal Oswal scaled personalized Portfolio Performance reporting with multi-lingual recommendations for their clients

Business challenge, barriers to communication of portfolio insights.

MOSL, caters to 100,000+ active customers across India, both retail and high net worth individuals (HNI). The company created monthly portfolio analysis reports for its diversified clientele to evaluate and communicate the performance of their investments. Unlike the HNI investors, the reports generated for retail customers simply tracked and compiled trading activity, inflows, outflows, positions, and balances in a tabular format. These transactional reports did not highlight any performance metrics. The broking firm could not provide personalized human financial advisors to its retail customers to make recommendations every step of the way. It was not a viable option.  And, not every customer was adept at understanding portfolio reports containing complex charts and tables. Even the financially savvy clients were unable to comprehend and analyze the performance of their investments in the market as compared to their peers. Moreover, since the majority of the investors belong to Maharashtra, Gujarat, and Tamil Nadu, they understood the regional languages better than English. Thus, creating and sharing portfolio analysis reports in one common language - English proved to create a barrier of communication between the portfolio managers and investors.

Issues Identified

• Significant resources required to provide human-advisory recommendations for each customer
• Tabular portfolio reports caused a communication gap between the clients and the portfolio managers
• Unable to send out investment reports to 1000s of customers every month
• Communication barriers in reaching a diverse set of customers with the reports being generated in English only

Curious to know what happened next? Unlock now to read the entire case study.

Phrazor solution, scaling personalized multi-lingual recommendations for a gamut of retail investors.

The business team recognized they needed a solution that would enable them to prepare effective portfolio analysis reports for each customer without significant human effort. They chose Phrazor to convert their complex portfolio-level datasets into personalized narrative-based reports, at scale.

• Using Phrazor, the financial services company eliminated the need for human advisors or financial experts. The team could now generate detailed portfolio analysis with personalized recommendations in the form of easy-to-understand narratives based on Natural Language Generation technology
• The personalized recommendations are auto-generated, based on the customer’s current portfolio performance and investment goals. The reporting automation tool considers different types of assets in a customer’s portfolio to evaluate its performance and highlights key insights like – warning signs, detailed recommendations, and market trends
• With Phrazor, the team at the stockbroking firm could easily scale their reporting process by producing thousands of reports at the speed of light with data of any size without disrupting the quality and consistency of the insights
• To eliminate the barrier of language and communication, Phrazor provides multi-lingual capabilities through which the firm could generate portfolio statements in 4 different languages– Hindi, English, Gujarati, and Tamil
• The Phrazor team also created an interactive real-time dashboard for the company’s customers and advisors, where they could easily log in, evaluate, and restructure the portfolio on a real-time basis. The provided recommendations could be applied with a click of a button
• The real-time portfolio dashboard was also incorporated in the company’s mobile application to increase customer convenience and provide ease of access irrespective of the time and location
• Phrazor also assisted the firm with multiple report-sharing options like a) Cover emails – which provide a summary of the portfolio insights b) Audio-Video reports – which compiles the entire portfolio analysis report with insights and recommendations into an audio-visual format c) PDFs – Customers can send the reports to themselves in a pdf format, at the click of a button from the dashboard itself
• To ensure data security and privacy, team vPhrase seamlessly integrated Phrazor with the company’s internal data sources via live APIs

Using Phrazor’s Analytical and Natural Language Generation capabilities, the MOSL team could: 

• Create easy-to-understand reports to help clients understand their investment performance a lot better, leading to an increase in the number of transactions
• The analysts deployed to prepare monthly portfolio reports were reallocated to work on higher-value tasks. This effectively led to the optimization of cost and human resources
• MOSL could seamlessly scale and reach out to many prospective customers at one go, based on their location, language, and investment goals
• Clients could easily anticipate their portfolio performance by creating various scenarios in the real-time interactive dashboards with zero dependencies

Company Overview

Motilal Oswal Financial Services (MOFSL), is a multi-faceted financial services company with a presence in over 550 cities through 2500+ business locations; managed by a team of over 6000 employees. It provides a range of diversified products and services across Retail and Institutional Broking, Private Wealth Management, Investment Banking, Private Equity, Asset Management and Home Finance. Motilal Oswal’s credo is wealth creation through knowledge for all its clients and stakeholders.

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Case Study: Patent Portfolio Quality Ranking and Analysis

Patent portfolio management strategy is an important factor in managing a firm’s intellectual property (IP) assets.  Successful portfolio management strategies can help prolong the life of a patent family and attract potential buyers or licensors.  

Because patent portfolio maintenance can become unwieldy and expensive as a firm grows, it is important to review one’s portfolio frequently to realign it with the firm’s goals.

In this case study, we discuss our patent portfolio strategy and analysis services and how it could potentially assist in streamlining and marketing a portfolio.

We were approached by a technology development and commercialization center for a government institution to assess the institution’s patent portfolio.

Patent Portfolio

The institution’s patent portfolio comprised 80 patents with issue dates from the past 6 years.  The overall portfolio was built from four different research groups and contained patents directed towards a wide range of high technologies and sciences, such as antennas, biomedical, polymers, lasers, optical systems, nanostructures, semiconductors, sensors, and surface coatings.

Our services were recruited to assess the patent portfolio and identify key targets for marketing and licensing.  Specifically, we were asked to determine how the patent parameters impacted the marketability of the portfolio, how attractive the patent portfolio was from a commercial perspective, the key indicators for assessing newly filed patent applications for marketing, and best practices for patent evaluation in view of marketing and licensing moving forward.

Taxonomy of the Patent Portfolio

Want more info on our Patent Portfolio Management services? Contact us today!

Team Assembled

GHB Intellect is a full-service intellectual property consulting firm.  Our strength lies within the quality and breadth of our team of experts who are especially selected to an individual project.  These experts have first-hand industry experience and possess the knowledge and background perfectly suited to support the requirements of a project.

As a first step in this project, we created a taxonomy of the subject matters involved in this portfolio and quickly discovered that it encompassed a wide breadth of technological/scientific fields.  As such, we hand-picked 14 subject matter experts from our team, all of whom were well-versed and well-experienced in the respective fields and industries of the subject matters.

In addition to subject matter experts who were assigned to review each patent for technical content and its potential applicability to various industries, three IP analysts were also assigned to the project to review each patent for potential legal and business risks.

To better suit client objectives in the most time-efficient and cost-effective manner, GHB Intellect can divide a project into a multi-step approach tailor-suited to the client’s goals.  This held true for this project, as there were numerous patents spanning multiple technologies and industries.  In consultation with the client, this patent portfolio evaluation project was performed in two phases.  The two-phase approach allowed us to save time spent on low-potential patents in favor of allocating more time on high-potential ones.  This, in turn, translated to cost savings to the client.

Creation of a Patent Scoring/Ranking System

To meet the client’s specific needs, we created a custom scoring system for assessing the client’s patent portfolio.  In conjunction with the client, the scoring system was established to provide a general rank of each patent based on a plurality of factors, including patent landscape, patent prosecution history, sufficiency of the specification and claims, number of claims, claim language and limitations, comparison of first to last claim set, broadness of the patent family, whether the patent family is open, likelihood of workarounds, ease of detection, applicability of the patent to various markets, ease of marketing, potential market size, and potential current use in the market, among others.  

Phase 1: Rapid Assessment of Patent Quality

Phase 1 involved performing a quality assessment of each individual patent across the patent portfolio, including a rapid review of the 80 patents in the client’s portfolio.  After rating each patent on several important attributes, it was assigned a rank of Low, Medium Low, Medium, Medium High, or High, which represented the overall attractiveness of each patent in an open market.  The ranks were given based on input by the subject matter experts and the IP analysts who reviewed and rated each patent, and who worked closely together to ensure accurate and consistent ranking across all parameters.

A spreadsheet report of Phase 1 was provided to the client, and 20 of the highest rated patents were selected for Phase 2 review.

Phase 2: Detailed Analysis of Patent Potential

Phase 2 of our analysis involved a detailed analysis of the 20 selected patents from technical, business, and legal perspectives.  Notably, we identified potential field(s) of use, potential market size, the significance of the patent, potential risk factors, and provided specific recommendations as to the direction to take each patent in terms of research and marketing.  Each patent was reassigned a composite score by IP analysts based upon an analysis of the potential market value, the significance and the risk factors identified for each patent, as well as the overall patent quality.

Our findings were updated in the spreadsheet from Phase 1.  In addition, we created easy-to-read one-page summaries for each of the 20 patents, highlighting their key indicators.  We also provided an executive summary of the project that not only documented the approach taken and the results obtained, it also provided strategic advice on the management/development of the portfolio going forward.

Sample One-Page Summary

Ultimately, our analysis assisted the client in identifying the most attractive patents within their portfolio for commercialization, the key indicators for that attractiveness, and best practices in evaluating patent and patent applications moving forward.

Managing a Patent Portfolio

Patent evaluation, particularly for large portfolios covering vast spaces in science and technology, require a multi-disciplined team and seasoned IP analysts to identify a patent’s significance, applicability, market, and risk factors.  GHB Intellect has over 500 experts in high-tech, science, finance, and IP.  By organizing the best and most appropriate team of experts (including technical, financial, legal, and business) for every project, and by utilizing best practices in IP evaluation, GHB Intellect is able to provide accurate and reliable patent portfolio management strategy and marketing suggestions. 

As a global Intellectual Property Consulting Firm, GHB Intellect offers a wide array of high-end services to support its clients in their IP matters.  We specialize in portfolio valuations, M&A advisory, patent litigation support, engineering, as well as IP development, management, and monetization.  Contact GHB Intellect today to get the reliable intellectual property consulting you can bank on.

Subject Matter Experts in This Case:

GHB Intellect has been providing IP technical and business consulting services since 2007, including turn-key IP assessments, development, management, valuation, and monetization support. Our goal is to align our client’s IP portfolio development and monetization activities with their business objectives.

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Dementia risk factors identified in new global report are all preventable – addressing them could reduce dementia rates by 45%

Affiliate Professor of Medicine, UW School of Medicine, University of Washington

Dean Emerita and Distinguished Professor of Nursing and Health, Drexel University

Disclosure statement

Eric B. Larson receives funding from National Institutes of Health, National Institute on Aging and UpToDate royalties for chapters that he writes and updates.

Laura N. Gitlin receives funding from the National Institute on Aging, Veterans Administration and also royalties from various books. She also is the creator of several online courses to train health providers in evidence-based care programs that she and her teams have tested and shown to be efficacious for which she and her university affiliations are entitled to training fees.

University of Washington and Drexel University provide funding as members of The Conversation US.

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Nearly half of all dementia cases could be delayed or prevented altogether by addressing 14 possible risk factors, including vision loss and high cholesterol.

That is the key finding of a new study that we and our colleagues published in the journal The Lancet.

Dementia , a rapidly increasing global challenge, affects an estimated 57 million worldwide, and this number is expected to increase to 153 million by 2050 worldwide . Although the prevalence of dementia is on the decline in high-income countries, it continues to increase in low- and middle-income countries .

This third updated report of the Lancet Commission on Dementia offers good news and a strong message: Policymakers, clinicians, individuals and families can be ambitious about prevention and reduce dementia risk; and for those living with dementia and their caregivers, support their quality of life using evidence-based approaches.

The new report confirms 12 previously identified potentially modifiable risk factors from two previous reports, published in 2017 and 2020 . It also offers new evidence supporting two additional modifiable risk factors: vision loss and high levels of low-density lipoprotein (LDL) cholesterol , often called “bad” cholesterol.

Our study of published evidence found that collectively, addressing 14 modifiable risk factors could potentially reduce the prevalence of dementia by 45% worldwide. Even greater risk reductions could be possible in low- and middle-income countries and for people with low income in higher-income countries given the higher prevalence of dementia , health disparities and risk factors in these populations.

The report further indicates that reducing these 14 risks can increase the number of healthy years of life and reduce the length of time with poor health in people with dementia.

Additionally, the report cites clinical trials showing that nonpharmacological approaches, such as using activities tailored to interests and abilities, can reduce dementia-related symptoms and improve quality of life .

We are a general internist and an applied sociologist and intervention scientist , and our work focuses on memory and wellness in older adults. Together with 25 other internationally recognized dementia experts under the leadership of psychiatry professor Dr. Gill Livingston , we carefully reviewed the evidence to derive recommendations for prevention, intervention and care.

Why it matters

The rapid growth of aging populations worldwide is a triumph of better public and personal health throughout the entire life span. Yet, given the lack of a dementia cure, this report highlights the importance of prevention as well as supporting quality of life for those with a dementia diagnosis.

In the new report, our team proposed an ambitious program for preventing dementia that could be implemented at the individual, community and policy levels and across the life span from early life through mid and late life. The key points include:

• In early life, improving general education.
• In midlife, addressing hearing loss, high LDL cholesterol, depression, traumatic brain injury, physical inactivity, diabetes, smoking, hypertension, obesity and excessive alcohol.
• In later life, reducing social isolation, air pollution and vision loss.

Together, these add up to the Lancet Commission on Dementia’s estimate that 45% of dementia risk can be reduced. And an abundance of new research shows that when risk factors are addressed, such as exposure to air pollution, they are linked with improved cognition and likely reduction of dementia risk .

New evidence supports the notion that in high-income countries, reducing dementia risk can translate to more healthy years, years free of dementia and a shorter duration of ill health for people who develop dementia.

What still isn’t known

The 45% reduction in dementia risk across the world’s population is based on a calculation that assumes that risk factors are causal and can be eliminated. It shows how dementia prevention is critical and the impact it would have on individuals and families.

The commission emphasized the need for more research to identify additional risk factors, test risk factor changes in clinical trials, provide guidance for public health efforts, and identify and evaluate strategies for implementing and scaling evidence-based programs that support people with dementia and caregivers.

The updated report has worldwide public health and research impact and is being widely disseminated. It serves as a guideline to clinicians and policymakers and outlines new research directions.

The Research Brief is a short take on interesting academic work.

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• Vision loss
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• Research Brief
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5 people charged in Matthew Perry's death, including 'Friends' actor's doctor, assistant

Five people have been charged in connection with " Friends " star Matthew Perry 's death from " the acute effects of ketamine " last October.

During a Thursday news conference , Martin Estrada, the U.S. attorney for the Central District of California, announced a shocking "number of charges against the five defendants."

Physician Salvador Plasencia, 42, and 41-year-old Jasveen Sangha, whom the DOJ's press release referred to as the "The Ketamine Queen" of North Hollywood, face 18 criminal counts for allegedly "distributing ketamine to Perry during the final weeks of the actor’s life."

Co-conspirators named in the case are Perry's live-in assistant Kenneth Iwamasa, 59; Dr. Mark Chavez, 54 and Erik Fleming, 54, who is described as Perry's acquaintance.

Iwamasa and Fleming pleaded guilty earlier this month to one count of conspiracy to distribute ketamine; Fleming pleaded guilty to an additional charge of distribution of ketamine resulting in death. Chavez "has agreed to plead guilty to one count of conspiracy to distribute ketamine," the Department of Justice said.

Iwamasa faces up to 15 years in prison; Fleming's charges come with a maximum sentence of 25 years. Chavez, who is scheduled to be arraigned Aug. 30, faces up to 10 years in prison.

USA TODAY has reached out to an attorney for Sangha for comment. Court records have not been updated with Plasencia's legal representative.

Matthew Perry's family speaks out: 'We look forward to justice taking its course'

US attorney: 'Defendants tried to cover up what they did'

"The defendants in this case knew what they were doing was wrong," Estrada said during Thursday's press conference.

Ketamine "is a drug that must be administered by medical professionals, and the patient must be monitored closely. That did not occur here," Estrada added, saying that after Perry's death, some of "these defendants tried to cover up what they did."

Estrada issued a warning to those who irresponsibly distribute and administer ketamine: "You are playing roulette with other people's lives, just like these five defendants here did to Mr. Perry."

In November 2022, Perry released his memoir "Friends, Lovers, and the Big Terrible Thing," a book that traced his origins with fame and an honest account of his highly publicized battle with alcoholism and drug addiction. His struggle with substances spanned decades.

Investigators detail the alleged actions that led to Matthew Perry's death

In a statement Thursday, U.S. Drug Enforcement Administration Administrator Anne Milgram said the five defendants "played a key role in (Perry's) death by falsely prescribing, selling, or injecting the ketamine."

"Matthew Perry’s journey began with unscrupulous doctors who abused their position of trust because they saw him as a payday, to street dealers who gave him ketamine in unmarked vials," Milgram said.

In a news release and a news conference Thursday, investigators laid out the moments that led to Perry's October death at his Los Angeles home.

According to a DOJ news release issued Thursday, Plasencia, the doctor, learned that Perry was interested in obtaining ketamine in September 2023.

New analysis: Should doctors be blamed for overdose deaths?

Later, Plasencia contacted Chavez, who used to operate a ketamine clinic, to obtain the anesthetic drug with the purpose to sell to Perry. According to investigators, Plasencia sent a text messages to Chavez that included, "I wonder how much this moron will pay" and "Lets find out."

According to investigators, on Oct. 28, 2023 — the day Perry died — his live-in assistant Iwamasa injected Perry with ketamine, as he did several times before, without proper medical licensure to complete the injections. The ketamine used in Perry's death was sold by Fleming and Sangha, officials allege, and administered with instructions and syringes provided by Plasencia.

Plasencia allegedly sold the drug to Iwamasa, although he was informed at least one week prior to Perry's death that his addiction to ketamine was "spiraling out of control." Later, Sangha allegedly texted Fleming to "delete all our messages" after news of Perry's death came out.

Later, the Los Angeles Police Department executed a search warrant at Sangha’s "stash house" and reported to have found evidence of drug trafficking, including approximately 79 vials of ketamine as well as several other drugs.

According to court records reviewed by USA TODAY, U.S. attorneys filed a complaint in March accusing Sangha of possession with intent to distribute methamphetamine. The federal case against her was updated with the first superseding indictment, which was unsealed Thursday and also named Plasencia, on Wednesday.

Remembering the iconic actor Why Matthew Perry was 'Friends' with all of us

More details emerge about fatal dose of ketamine administered by Matthew Perry's assistant

On Sept. 30, Iwamasa learned how to inject ketamine after Dr. Plasencia, who was nicknamed "Dr. P," administered two shots of ketamine" to Perry and then taught the personal assistant how to make injections and left behind a vial for him. For days, Iwamasa also used coded language to communicate with co-conspirators to obtain more ketamine.

But two weeks before his death, on Oct. 12, investigators say Plasencia administered "a large dose of ketamine" to Perry, which caused "an adverse medical reaction" that led to a blood pressure spike which caused Perry to "freeze up" where he "could not speak or move."

According to the plea agreement, Plasencia allegedly told Iwamasa "let's not do that again."

Matthew Perry's last days: Actor given fatal ketamine dose by assistant, court docs show

The court documents also appear to suggest that Iwamasa and Perry planned to take a break from ketamine use as Plasencia, who is listed as "co-conspirator 1" in court documents, texted Iwamasa: “Hi. I know you mentioned taking a break.I have been stocking up on the meanwhile. I am not sure when you guys plan to resume but in case its when im out of town this weekend I have left supplies with a nurse of mine."

On October 28, 2023, the day that Perry died, Iwamasa allegedly injected him with a shot of ketamine at 8:30 a.m. and again in the afternoon at 12:45 p.m. as Perry watched a movie. Then, about 40 minutes later, Perry asked his personal assistant to prepare his hot tub and “shoot me up with a big one," in reference to another injection of ketamine.

Iwamasa later injected Perry with a third syringe of ketamine and gave it to him "in or near the jacuzzi." According to the authorities' timetable, Perry had received three ketamine shots in a five-hour period. Later, Perry was found dead.

Matthew Perry's cause of death

On Oct. 28, 2023, the Los Angeles Fire Department responded to Perry's Pacific Palisades home at 4:07 p.m. and found "an adult male unconscious in a stand-alone jacuzzi." Responding officers pronounced him dead at 4:17 p.m.

"A rapid medical assessment, sadly, revealed the man was deceased prior to first responder arrival," Nicholas Prange, an LAFD spokesperson, told USA TODAY in a statement on Oct. 30.

In December, more than a month after Perry's death, the Los Angeles County Medical Examiner's office released Perry's autopsy report, which was obtained by USA TODAY. His death was ruled an accident, with the cause being " the acute effects of ketamine ." Contributing factors were drowning, coronary artery disease and the effects of buprenorphine.

Buprenorphine is "an opioid-like drug used in the treatment of opioid addiction as well as acute and chronic pain," according to Perry's 29-page autopsy report. There were no signs of "fatal trauma and no foul play suspected," per the report.

Matthew Perry death arrests made: Watch press conference

Ketamine levels on par with general anesthesia were in Matthew Perry's system

Ketamine is a "dissociative anesthetic that has some hallucinogenic effects" and "distorts the perception of sight and sound,"  according to the DEA's website. The medical examiner said the amount of ketamine found in his system was as high as 3,540 nanograms per milliliter. "Levels for general anesthesia are typically in the 1,000-6,000 ng/ml ranges," the report notes.

There were no pills, drugs or medications found near the pool, according to his autopsy. Perry, who was reportedly sober for 19 months, didn't have alcohol or drugs such as methamphetamine, cocaine, heroin and fentanyl in his system.

The autopsy report: Matthew Perry's cause of death revealed

Perry was "reported to be receiving ketamine infusion therapy for depression and anxiety," according to the report, and his last session was reportedly one and a half weeks before his death. But, the report notes, "the ketamine in his system at death could not be from that infusion therapy, since ketamine’s half-life is 3 to 4 hours, or less." The autopsy also said the method of intake was unclear.

"At the high levels of ketamine found in his postmortem blood specimens, the main lethal effects would be from both cardiovascular overstimulation and respiratory depression," the report reads.

"Drowning contributes due to the likelihood of submersion into the pool as he lapsed into unconsciousness; coronary artery disease contributes due to exacerbation of ketamine induced myocardial effects of the heart."

Delineating bacterial genera based on gene content analysis: a case study of the Mycoplasmatales-Entomoplasmatales clade within the class Mollicutes

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Genome-based analysis allows for large-scale classification of diverse bacteria and has been widely adopted for delineating species. Unfortunately, for higher taxonomic ranks such as genus, establishing a generally accepted approach based on genome analysis is challenging. While core-genome phylogenies depict the evolutionary relationships among species, determining the correspondence between clades and genera may not be straightforward. For genotypic divergence, percentage of conserved proteins (POCP) and genome-wide average amino acid identity (AAI) are commonly used, but often do not provide a clear threshold for classification. In this work, we investigated the utility of global comparisons and data visualization in identifying clusters of species based on their overall gene content, and rationalized that such patterns can be integrated with phylogeny and other information such as phenotypes for improving taxonomy. As a proof of concept, we selected 177 representative genome sequences from the Mycoplasmatales-Entomoplasmatales clade within the class Mollicutes for a case study. We found that the clustering patterns corresponded to the current understanding of these organisms, namely the split into three above-genus groups: Hominis, Pneumoniae, and Spiroplasma-Entomoplasmataceae-Mycoides (SEM). However, at the genus level, several important issues were found. For example, recent taxonomic revisions that split the Hominis group into three genera and Entomoplasmataceae into five genera are problematic, as those newly described or emended genera lack clear differentiations in gene content from one another. Moreover, several cases of mis-classification were identified. These findings demonstrated the utility of this approach and the potential application for other bacteria.

Competing Interest Statement

The authors have declared no competing interest.

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