#database tool

[knowledgehound]

In this digital world, companies rely on survey data to gather information about their targeted audience and their preferences. Businesses employ different methods to collect the survey data and analyze it. There are various mediums used to collect opinions and feedback from customers. While conducting a survey, researchers often choose multiple sources to collect data. KnowledgeHound shares the different methods used to collect the data.,,Learn more

[cuties-in-codices]

Where do you find these manuscripts? Is it like a website or do you find it randomly??

hey, thanks for the curiosity! lenghty answer below the cut :)

1)

medieval manuscripts are typically owned by libraries and showcased on the library's websites. so one thing i do is i randomly browse those digitized manuscript collections (like the collections of the bavarian state library or the bodleian libraries, to name just two), which everybody can do for free without any special access. some digital collections provide more useful tools than others (like search functions, filters, annotations on each manuscript). if they don't, the process of wading through numerous non-illustrated manuscripts before i find an illustrated one at all can be quite tedious.

2)

there are databases which help to navigate the vast sea of manuscripts. the one i couldn't live without personally use the most is called KdIH (Katalog der deutschsprachigen illustrierten Handschriften des Mittelalters). it's a project which aims to list all illustrated medieval manuscripts written in german dialects. the KdIH provides descriptions of the contents of each manuscript (with a focus on the illustrations), and if there's a digital reproduction of a manuscript available anywhere, the KdIH usually links to it. the KdIH is an invaluable tool for me because of its focus on illustrated manuscripts, because of the informations it provides for each manuscript, and because of its useful search function (once you've gotten over the initial confusion of how to navigate the website). the downside is that it includes only german manuscripts, which is one of the main reasons for the over-representation of german manuscripts on my blog (sorry about that).

3)

another important database for german manuscripts in general (i.e. not just illustrated ones) is the handschriftencensus, which catalogues information regarding the entirety of german language manuscripts of the middle ages, and also links to the digital reproductions of each manuscript.

4)

then there are simply considerable snowball effects. if you do even just superficial research on any medieval topic at all (say, if you open the wikipedia article on alchemy), you will inevitably stumble upon mentions of specific illustrated manuscripts. the next step is to simply search for a digital copy of the manuscript in question (this part can sometimes be easier said than done, especially when you're coming from wikipedia). one thing to keep in mind is that a manuscript illustration seldom comes alone - so every hint to any illustration at all is a greatly valuable one (if you do what i do lol). there's always gonna be something interesting in any given illustrated manuscript. (sidenote: one very effective 'cheat code' would be to simply go through all manuscripts that other online hobbyist archivers of manuscript illustrations have gone through before - like @discardingimages on tumblr - but some kind of 'professional pride' detains me from doing so. that's just a kind of stubbornness though. like, i want to find my material more or less on my own, not just the images but also the manuscripts, and i apply arbitrary rules to my search as to what exactly that means.)

5)

whatever tool or strategy i use to find specific illustrated manuscripts-- in the end, one unavoidable step is to actually manually skim through the (digitized) manuscript. i usually have at least a quick look at every single illustrated page, and i download or screenshot everything that is interesting to me. this process can take up to an hour per manuscript.

---

in conclusion, i'd say that finding cool illuminated manuscripts is much simpler than i would have thought before i started this blog. there are so many of them out there and they're basically just 'hidden in plain side', it's really astounding. finding the manuscripts doesn't require special skills, just some basic experience with/knowledge of the tools available. the reason i'm able to post interesting images almost daily is just that i spend a lot of time doing all of this, going through manuscripts, curating this blog, etc. i find a lot of comfort in it, i learn a lot along the way, and i immensely enjoy people's engagement with my posts. so that's that :)

[necro-hamster]

ppl defending ai art by completely ignoring the genuine major issues that people have with it and pretending like ppl r just mad because they're Art Elitists and think that art should only be made through Suffering instead of being easy are some of the most embarrassing ppl tumblr has been recommending to me lately

[yoshistory]

I wanna make more sense of Petscop just from like. my brain and not looking things up and trying to see what I can form. But I do think it's a really obtuse reading of it to assert that Paul and Care and "Pall" are not the same person. But I'm trying to entertain the thought just to look at it from another angle

[smallerthanzer0]

(M:I Dead Reckoning spoilers)

OH

i briefly forgot that cyber crime exists and thought the movie was telling us that Benji straight up killed a man before joining the IMF

[coder23-data]

The Data Migration Odyssey: A Journey Across Platforms

As a database engineer, I thought I'd seen it all—until our company decided to migrate our entire database system to a new platform. What followed was an epic adventure filled with unexpected challenges, learning experiences, and a dash of heroism.

It all started on a typical Monday morning when my boss, the same stern woman with a flair for the dramatic, called me into her office. "Rookie," she began (despite my years of experience, the nickname had stuck), "we're moving to a new database platform. I need you to lead the migration."

I blinked. Migrating a database wasn't just about copying data from one place to another; it was like moving an entire city across the ocean. But I was ready for the challenge.

Phase 1: Planning the Expedition

First, I gathered my team and we started planning. We needed to understand the differences between the old and new systems, identify potential pitfalls, and develop a detailed migration strategy. It was like preparing for an expedition into uncharted territory.

We started by conducting a thorough audit of our existing database. This involved cataloging all tables, relationships, stored procedures, and triggers. We also reviewed performance metrics to identify any existing bottlenecks that could be addressed during the migration.

Phase 2: Mapping the Terrain

Next, we designed the new database design schema using schema builder online from dynobird. This was more than a simple translation; we took the opportunity to optimize our data structures and improve performance. It was like drafting a new map for our city, making sure every street and building was perfectly placed.

For example, our old database had a massive "orders" table that was a frequent source of slow queries. In the new schema, we split this table into more manageable segments, each optimized for specific types of queries.

Phase 3: The Great Migration

With our map in hand, it was time to start the migration. We wrote scripts to transfer data in batches, ensuring that we could monitor progress and handle any issues that arose. This step felt like loading up our ships and setting sail.

Of course, no epic journey is without its storms. We encountered data inconsistencies, unexpected compatibility issues, and performance hiccups. One particularly memorable moment was when we discovered a legacy system that had been quietly duplicating records for years. Fixing that felt like battling a sea monster, but we prevailed.

Phase 4: Settling the New Land

Once the data was successfully transferred, we focused on testing. We ran extensive queries, stress tests, and performance benchmarks to ensure everything was running smoothly. This was our version of exploring the new land and making sure it was fit for habitation.

We also trained our users on the new system, helping them adapt to the changes and take full advantage of the new features. Seeing their excitement and relief was like watching settlers build their new homes.

Phase 5: Celebrating the Journey

After weeks of hard work, the migration was complete. The new database was faster, more reliable, and easier to maintain. My boss, who had been closely following our progress, finally cracked a smile. "Excellent job, rookie," she said. "You've done it again."

To celebrate, she took the team out for a well-deserved dinner. As we clinked our glasses, I felt a deep sense of accomplishment. We had navigated a complex migration, overcome countless challenges, and emerged victorious.

Lessons Learned

Looking back, I realized that successful data migration requires careful planning, a deep understanding of both the old and new systems, and a willingness to tackle unexpected challenges head-on. It's a journey that tests your skills and resilience, but the rewards are well worth it.

So, if you ever find yourself leading a database migration, remember: plan meticulously, adapt to the challenges, and trust in your team's expertise. And don't forget to celebrate your successes along the way. You've earned it!

[latest-info]

How to Access Exclusive Research Archives Online

In the digital age, exclusive research archives have become invaluable resources for academics, professionals, and curious minds alike.

In the digital age, exclusive research archives have become invaluable resources for academics, professionals, and curious minds alike. These archives house a wealth of information, often containing rare and comprehensive collections that are not readily available to the general public. Accessing these archives can seem daunting, but with the right approach, it is entirely feasible. Here’s a…

[aceteling]

okay, what am i doing here

[networksupported]

sinking my head into my hands <- incorrect ai opinions blazed on dash

[fiendfriend]

Love making big compilations of links to web pages and pdfs

Need to get back to coding my stupid little website so that I might compile all of my compilations

[vaultsixtynine]

happy moon landing day AND happy day i finally get my prototype tool out of dev finally.

[knowledgehound]

Effective Data Insights — A Game Changer for Businesses

Data insights are crucial for businesses to make informed decisions and remain competitive in the ever-evolving market. With the increase in the volume, variety, and velocity of data, it has become necessary for organizations to have the capability to analyze data and derive insights that help them make data-driven decisions. This article will explore the importance of data insights for businesses, steps to achieving effective data insights, best practices, tools, challenges, and future of data insights.

Introduction to Data Insights

According to KnowledgeHound, Data insights refer to the process of analyzing and interpreting data to extract meaningful information that can be used to make informed decisions.

It involves using various tools and techniques to identify patterns, trends, and relationships in data. There are many resources available for beginners who want to learn about data analytics, including online courses and guides.

These resources cover topics such as the role of a data analyst, tools used in data analysis, and the entire data analysis process. With the increasing demand for professionals with skills in data analytics, learning this field can be a great way to kickstart a career.

Importance of Data Insights for Businesses

Data insights are crucial for businesses as they provide valuable information that can be used to make informed decisions. By analyzing customer data from various channels, businesses can gain insights into customer behavior and preferences, which can help them provide a more personalized experience.

Historical data analysis can also help businesses anticipate fluctuations in consumer demand and make better business decisions. Companies that embrace data analytics initiatives can experience significant financial returns. Data analytics helps businesses optimize their performance by identifying areas for improvement and making strategic investments.

Implementing data analytics into the business model means companies can stay competitive in today’s market by making informed decisions based on real-time data.

Steps to Achieving Effective Data Insights

Achieving effective data insights involves several steps.

Firstly, it is important to align the data strategy with the business strategy and identify relevant business drivers that could be positively impacted by data and analytics.

Secondly, organizations need to implement processes such as data cataloging and governance and embrace culture changes to achieve effective analytics programs.

Thirdly, businesses should use deep learning to get value from unstructured data.

Finally, carrying out various analyses on the data is essential to obtain insights. The four types of data analysis include descriptive, diagnostic, predictive, and prescriptive analysis.

By following these steps, businesses can turn their data into actionable insights that can be used to make informed decisions.

Best Practices for Data Insights

To achieve the best results from data insights, businesses should follow some best practices.

It is important to define business objectives and identify the key performance indicators that will be used to measure success.

Building high-performance analytics teams and promoting data literacy within the organization can help ensure that everyone understands how to use data effectively.

Collecting, storing, and organizing data correctly is essential for accurate analysis.

Segmenting the audience can help businesses gain a better understanding of their customers’ behavior and preferences.

Using data storytelling can help promote insights by making complex data more accessible and understandable.

Utilizing new infrastructure technology and more advanced analytics can help businesses stay ahead of the competition.

By following these best practices, businesses can turn their data into actionable insights that drive growth and success.

Tools for Data Insights

There are many tools available for data insights that businesses can use to analyze and interpret their data. Some of the most widely used business analytics tools include Microsoft Power BI, Tableau, Qlik Sense, Excel and KnowledgeHound.

These tools are designed to help businesses visualize and analyze their data to gain insights into customer behavior, market trends, and other key metrics. These tools offer a range of features such as data visualization, predictive modeling, machine learning algorithms, and more.

By using these tools effectively, businesses can turn their data into actionable insights that drive growth and success.

Challenges in Data Insights

There are several challenges that businesses face when it comes to data insights.

Managing vast amounts of data can be a challenge, as it requires the right tools and techniques to analyze and interpret the data effectively.

Seelecting the right analytics tool can be difficult, as there are many options available and each has its own strengths and weaknesses.

Data visualization can be challenging, as it requires businesses to present complex data in a way that is easy to understand.

Dealing with data from multiple sources can be a challenge, as it requires businesses to integrate different types of data into a single system.

Low-quality data can also pose a challenge, as it can lead to inaccurate insights and decisions.

Other challenges include cultural dynamics within the organization, inaccessible data, lack of system integration, excessive costs, complexity and skills gaps.

By addressing these challenges effectively through proper planning and implementation of best practices for data insights, businesses can turn their data into actionable insights that drive growth and success.

Future of Data Insights

The future of data insights is promising, with several trends emerging that are expected to shape the industry in the coming years.

Businesses are expected to emphasize business intelligence, edge data, and cloud-native technologies.

Data democratization, artificial intelligence, and real-time data analytics are expected to become more prevalent.

Adaptive AI systems and metadata-driven data fabric are also expected to gain traction.

Real-time automated decision making and no-code solutions are also predicted to be important trends in the future of data insights.

Data quality and observability will continue to be important factors in ensuring accurate insights from data analysis.

By staying up-to-date with these trends and adopting new technologies and techniques as they emerge, businesses can stay ahead of the competition and turn their data into actionable insights that drive growth and success.

Also Read: Different Types of Survey Data Collection Methods You Should Know

[ritualvirtuality]

soooo i just finished cataloging all of our books (at least i think so) so here's a chart and some superlatives!

some explanations on the above chart: we use a tagging system for topics, so one book can be in multiple topics (and as a result multiple supertopics). yes, the supertopics are a little strange, but we chose them to best fit our library so that books would be generally well distributed between them. also i really wish i could figure out how to change where the labels are pointing but unfortunately idk google sheets charts that well...

and thats some superlatives for our library. the dates are original publication dates (for the case of Medea, its the publication of that specific translation).

more of this may be coming! if im interested in doing it lol

[iipsearch]

How to Perform a Chemical Structure Search: A Comprehensive Guide | IIP Search

A chemical structure search is a powerful tool for identifying molecular data based on structural configurations. This blog provides a detailed guide on how to perform such searches, covering essential steps like selecting the right database, inputting chemical structures, and interpreting results. It highlights the importance of these searches in research, intellectual property, and industry applications. Additionally, the blog explores advanced techniques, top tools, and emerging trends in the field, making it a comprehensive resource for researchers and professionals seeking accurate and efficient chemical analysis.

Ready to streamline your chemical research and achieve exceptional results? Visit https://iipsearch.com/ today to learn how our expert solutions can elevate your projects to new heights. Explore our services and experience the difference that expertise makes!

[jcmarchi]

Nicole Clark, CEO & Founder of Trellis – Interview Series

New Post has been published on https://thedigitalinsider.com/nicole-clark-ceo-founder-of-trellis-interview-series/

Nicole Clark, CEO & Founder of Trellis – Interview Series

Nicole Clark, CEO and founder of Trellis, created the legal analytics platform to address challenges she faced as a litigator. Drawing from her experience in business litigation, she began aggregating state trial court data to tailor legal arguments and improve case outcomes. Recognizing its potential, she expanded Trellis to democratize access to legal insights.

With an unconventional background, including early college enrollment and degrees in journalism and law, Clark now shares her expertise widely while residing in Los Angeles with her daughter and her love for plants.

Trellis is a legal analytics platform focused on improving accessibility to state trial court records and legal data. By providing tools to analyze judicial rulings, legal trends, and opposing counsel strategies, Trellis supports legal professionals in making informed decisions. Its mission centers on enhancing transparency and accessibility within the judicial system.

What role does democratizing access to legal data play in Trellis’ mission, and why is it so important?

Democratizing access to law by making state trial court records and legal data more accessible is central to our core mission at Trellis. The state court system is actually the largest court system in the world, yet historically, it’s been incredibly fragmented and difficult to navigate. This lack of transparency has created an uneven playing field where only those with substantial resources could access and analyze this crucial data effectively.

By making this data searchable and accessible, Trellis brings greater transparency to our judicial system which benefits firms of all sizes, from solo practitioners to large firms. By providing access to state trial court data and insights, we empower attorneys to make more informed decisions, better serve their clients, and ultimately contribute to a more equitable justice system. Our mission goes beyond accessibility – it’s about transforming how the legal profession interacts with data to create lasting impact.

Your inspiration for Trellis came from a late night spent writing a motion for summary judgment, where a past ruling by the judge became a game-changer for your case. Can you walk us through that moment and how it evolved into the idea of building a platform to aggregate state trial court data?

That night was truly a turning point for me. While drafting a complex motion for summary judgment, I struggled because I wasn’t familiar with the judge assigned to the case. A colleague shared an old ruling from the same judge and it was like landing a detailed study guide for a final exam.

The ruling gave me insights into how the judge thought, enabling me to tailor my arguments accordingly. I won that motion, and it was a lightbulb moment: if one document could transform my strategy, imagine the possibilities with greater access to trial court data.

This experience planted the seed for Trellis. I started aggregating state trial court data with the help of software developers for my own practice, focusing initially on tentative rulings from judges in Southern California. The results were so impactful that I knew this tool couldn’t remain my personal secret weapon.

Trellis was born to bring this same level of insight to attorneys everywhere, making it easy for them to analyze judicial tendencies, craft winning strategies, and save countless hours of manual research.

Can you talk about the early days of developing the Trellis database and how you identified the most valuable features for attorneys?

The early days were driven by my firsthand experience as a litigator. I understood that attorneys face recurring pain points, and I knew we needed to solve those first. Our initial focus was on making trial court records searchable and creating judge analytics to uncover ruling patterns.

From the beginning, it became clear that the real value lay in taking these foundational features to the next level. Trellis now enables attorneys to do far more than just search for cases, we help with strategic decisions throughout the life of a case—from researching similar cases and understanding judge tendencies to tracking newly filed litigation and analyzing opposing counsel’s patterns.

We focused on building features that would help attorneys work more efficiently and make more informed decisions, always keeping in mind that time is an attorney’s most valuable resource.

Trellis is a prime example of verticalized AI applications. How does specializing in legal analytics make Trellis AI different from more generalized AI tools like ChatGPT?

We recently launched Trellis AI, the only productivity platform tailored for trial court litigation. What sets Trellis AI apart is that it’s built specifically for litigators, by litigators, and is powered by the largest state trial court database in existence. Unlike generalized AI tools, we’re not just applying language models to legal work – we’re combining AI with hundreds of millions of actual court motions, briefs, and documents that represent countless hours of attorney work product and judicial decisions.

Trellis AI is unique because it’s built upon trial court data—where 99.7% of cases actually take place. While other legal AI products might rely on appellate case law or general legal knowledge, we’re focused on the courts where litigators actually practice day-to-day. This focus allows us to provide actionable insights based on real-world litigation experience, not just theoretical legal principles. Trellis AI transforms trial court data into a strategic advantage for attorneys.

Trellis offers tools like motion drafting, case assessments, and judge analytics. How do these tools transform the day-to-day workflows of attorneys?

Our tools are designed to address the real challenges attorneys face in their daily practice. For example, our judge analytics allow attorneys to understand a judge’s tendencies —how they’ve ruled on similar motions, their case duration averages, and tendencies in specific practice areas. This helps set realistic client expectations and develop effective strategies from day one.

Our AI tools streamline time-consuming tasks like document review, creating timelines, and analyzing arguments. Instead of spending hours manually reviewing documents or researching similar cases, attorneys can get instant and actionable insights that help them make strategic decisions. These tools don’t replace attorney judgment—they enhance it by offering better tools to exercise that judgment more efficiently and effectively.

Could you elaborate on the process behind integrating Trellis’ state trial court data into actionable insights for attorneys? 

At Trellis we’re focused on making complex data accessible and actionable. When we aggregate court data, we’re not just collecting it – we’re structuring it in ways that directly answer the most pressing questions attorneys face. For example, an attorney might want to understand a judge’s grant rates on specific types of motions, or see how often opposing counsel has handled similar cases along with their success rates.

The key has been to maintain the context that makes this data valuable. We’re not just showing numbers – we’re providing direct links to the underlying cases and documents, so attorneys can dive deeper when needed. This combination of high-level analytics and granular detail allows attorneys to move seamlessly between strategic overview and tactical implementation.

With concerns about AI “hallucination” in legal outputs, how does Trellis maintain accuracy and reliability in its recommendations?

Accuracy is non-negotiable for Trellis AI. Unlike generalized AI, which may generate speculative or unreliable outputs, Trellis AI is grounded in verified court data. Our insights are derived from real court rulings, motions, and filings—eliminating much of the guesswork that can lead to hallucinations associated with other AI models.

What sets Trellis AI apart is that it was built upon actual court records and real case outcomes. When our system delivers insights or recommendations, they are based on an analysis of cases, motions, and rulings that have actually occurred in state trial courts. While we encourage users to review the output, our approach of combining AI with actual court data helps minimize the risk of hallucination that can occur with generic AI tools.

To ensure reliability, our team of attorneys has rigorously tested our models with thousands of documents. Trellis AI goes beyond providing answers—it delivers tools attorneys can trust. Every insight is backed by data that is verifiable, making Trellis AI not just powerful, but also dependable and indispensable for legal professionals.

What were the biggest challenges in transitioning from legal practice to building a technology company?

The transition required a complete mindset shift. As a litigator, I was trained to focus on individual cases and specific legal arguments. Building a technology company, however, required thinking on a much larger scale—developing solutions that could serve thousands of attorneys across diverse practice areas and jurisdiction

One of the most significant challenges was addressing the fragmented nature of state trial courts. Each jurisdiction operates with its own unique systems, formats, and processes, making it incredibly complex to create a unified, searchable database. Solving these technical challenges while ensuring the platform remained intuitive for attorneys was a delicate balancing act.

We prioritized simplicity without sacrificing sophistication, building powerful analytics tools that provide deep insights yet remain accessible with just a few clicks. This combination of user-friendly design and advanced technology has been key to empowering attorneys to work smarter and more efficiently.

Where do you see Trellis in the next five years, particularly as AI continues to advance?

Our vision is to continue revolutionizing how attorneys work with state trial court data. We’re currently expanding our coverage across more jurisdictions while developing increasingly sophisticated AI tools to help attorneys work more efficiently and effectively. We have coverage for 45 states now, and we’re actively working to expand our reach.

As AI technology advances, we’ll be able to provide even more nuanced insights and predictions about case outcomes, while maintaining our focus on accuracy and reliability. The future isn’t about replacing attorney judgment—it’s about augmenting it with better data and more sophisticated analytics. Whether it’s helping a solo practitioner prepare for trial or equipping a large firm with data-driven insights, our goal is to make practicing law smarter, fairer, and more accessible.

What advice would you give to legal professionals who are considering leveraging AI tools in their practice?

My advice is to view AI tools as enhancers of your expertise rather than replacements for it. Focus on solutions specifically designed for legal professionals—tools that deliver tangible value to your daily workflow. The best legal AI tools should save you time, streamline tasks, and support more informed decision-making without compromising the quality of your work.

Start by identifying pain points in your practice where better data or automation could make a difference. Whether it’s conducting research, reviewing documents, or developing case strategies, choose tools tailored to address those specific needs. Prioritize tools that emphasize accuracy and provide transparency about their data sources and methodologies.

Ultimately, the goal of legal technology isn’t to redefine what attorneys do but to help them do it more efficiently and effectively. The most successful attorneys will be those who learn to effectively combine their legal expertise with these new tools while maintaining their professional judgment and ethical obligations.

Thank you for the great interview, readers who wish to learn more should visit Trellis.

[this-is-not-a-slow-burn]

hate what people did to the dead dove tag