Forem: Fischerbach

Top 3 Low- and No-code Databases for Creative Entrepreneurs

Fischerbach — Mon, 26 Jul 2021 07:45:35 +0000

Interactive spreadsheets help free up your time

If you are like me and run your own practice (business, freelancing, publishing, whatever you want to call it), you probably use some form of a spreadsheet. I started managing my finances, client relationships, time, and other things by creating spreadsheets in Google Sheets (and even before that in classic Excel).

The advantage of Google Sheets is undoubtedly their accessibility from any platform equipped with a modern browser. Furthermore, Sheets can be extended using Google Apps Script (the equivalent of Visual Basic from Microsoft Office, I believe).

Why creators need no-code platforms

Google Sheets are great, but the more I’ve used them, I’ve noticed a certain regularity. Every time I set up a new sheet to manage some project, there was a certain group of actions and elements that repeated between different sheets:

Date columns for deadlines & marking updates,
Columns with dropdown select,
True/false columns in form of checkboxes,
VLOOKUP and similar search functions,
Pivot tables.

Google Sheets, as spreadsheet software, is a general-purpose tool. Therefore, creating even relatively simple interfaces, although easy, was quite labour intensive.

Aesthetic considerations were also behind the search for alternatives. If I spend several hours in a tool, I would prefer it to be visually satisfying.

Smart spreadsheets

The category, to which all software discussed today belongs, does not have an established name. They are often referred to as interactive or smart spreadsheets. They are usually called (even by their creators) as Airtable alternatives 😅

In other words, tools for creating interactive online databases without technical experience. Interactive sheets provide the sweet spot between flexibility and development speed, by lowering the barriers to database creation. Thanks to that anyone, who know how to work with a spreadsheet, can also work with databases. They allow you to create tables with business data and automatically recalculated fields, just like classic spreadsheets.

But at the same time, they have a set of functions that go further. For example, if a table contains a date column, you can overlay its content on a calendar view. The key point here is that whenever you use one of the platforms described below, you are using ready-made elements, blocks and functionalities, prepared by their developers.

You drag and drop or attach those elements to your project.

At the same time, you retain the flexibility of a classic spreadsheet because you have access to APIs and libraries in popular programming languages. You or your software engineer will be able to adapt the tool to a specific business case.

But why self-hosted?

However, before you trash all your existing spreadsheets, there is one more thing to consider. Most of the solutions available on the market are very convenient, contain a certain minimum set of functions and have a low entry barrier. Those causes make the temptation to base your business logic on those tools. But what if a particular service has a failure or even ceases to exist? Your data, your workflows and your automation can disappear irretrievably.

If, on the other hand, ...

Ad Verification: How to Check Display Advertising Quality?

Fischerbach — Fri, 23 Jul 2021 18:34:11 +0000

Does IP quality matter?

Digital display advertising relies on the real-time exchange of ad impressions. In the programmatic ecosystem, each page visit could be monetized through an auction between the publisher (seller) and advertisers (buyers).

They make transactions through private deals, real-time auctions, or a hybrid of the two. Despite generally positive market adoption (in the U.S. share of programmatic reached 85% of all spendings), advertisers still have doubts due to the complexity and opacity of certain mechanisms.

The purchase of ad impressions is characterised by an information asymmetry, to the advantage of publishers. As the display advertising market grows, there is a stronger temptation to defraud advertisers’ money by exploiting these complexities.

Today, using a similar tool, we will take a closer look at the display campaign purchased in the programmatic system and do basic ad verification using IP information.

How to Localize Banner Ad Campaign

Fischerbach — Thu, 22 Jul 2021 13:08:00 +0000

Depending on your industry, the language of communication with potential clients can be more or less important. Every content must be in the language with which your users feel most comfortable.

Translating your banner advertisement into other languages can really impact the effectiveness of your marketing creatives.

In this article, we’re not only going to provide some advice on translating advertising creatives, but also show you how to make this process much more streamlined. For more tech-savvy marketers, I will show how to easily manage HTML translations of banners and how to automatically display the appropriate language version.

How to Create a Dashboard for Free with Google Sheets and C3.js

Fischerbach — Thu, 22 Jul 2021 08:03:24 +0000

We often have some business data that we need to track. We collect, process and store it in spreadsheets to then create charts and diagrams. However, sometimes there is a need to go out to a non-technical audience. There are many services for building decent-looking charts and dashboards, such as Tableau, Qlikview, or Google Data Studio.

However, they are often too expensive or too limited to be useful for any case. Fortunately, it is possible to serve static HTML and JavaScript files directly from Google Apps Script.

In this article, I show you how to create a simple dashboard using data from Google Sheet and C3.js. First, we will set up a web application template in Google Apps Script. Next, we will integrate it with C3.js. Then, we will fetch data from Google Sheets (e.g. to update information in the dashboard) and insert it into the template. This project may become a scaffold for creating many different dashboards and visualizations.

How to create animated meteogram

Fischerbach — Wed, 21 Jul 2021 20:41:48 +0000

Using Python and Meteoblue weather newsletter

Meteogram is a graphical presentation of meteorological variables (observed or forecasted) through time, for a specific location. The meteogram below was created by combining several forecasts from Meteoblue’s newsletter.

Each “frame” contains 5-day meteogram with 3 simple graphs for a specific location:

Temperature chart with weather pictograms. The time from sunrise to sunset is indicated in light yellow.
Clouds in different altitudes: from a few clouds (light grey) to overcast (dark grey). Dark blue bars show hourly precipitation and light blue showers. An asterisk indicates snowfall.
Forecasts of wind speeds are blue and gusts are green. The arrowheads point in the same direction as the wind.

In this article, you will find instructions on how to create similar animation for your neighbourhood.

How to add content recommendations to website

Fischerbach — Wed, 21 Jul 2021 20:24:47 +0000

How to add content recommendations to website

Show users what they want (even though they don’t even know what they want)

Personalized content proposals are now an established element of the Web. Most social media serve content to their users based on multiple touchpoints of the user’s interaction with the platform. (Some of them also track the user outside their pages, which has caused a whole discussion about privacy and blocking cross-domain tracking.) Usually, the aim is to increase some interaction rate (i.e. measured by the number of visits, purchases or other actions per user).

Online shops increase their revenue with clever recommendations of products that appear at every stage of the sales funnel. But non-retail sites can also benefit from the advantages of recommender systems. If you run a website that provides content, you can use content recommendations to maintain user attention and increase visits.

In this article, using an example of a movie database web site, I’ll show you how to add content recommendations to your website. We’ll discuss basic approaches to this and then use a SaaS called Pipeless, which allows you to create a database with built-in recommendation algorithms.

Build Social Network on Top of Your Website

Fischerbach — Wed, 21 Jul 2021 20:21:56 +0000

Build Social Network on Top of Your Website

How to add social features to existing web application

Social media apps have already taken up a significant portion of our lives and the app market, and their numbers continue to grow. A recent hot topic was Clubhouse and its voice chat features. The social networking giants are already imitating them.

This is a common pattern in this industry. An alternative player emerges, using something new as a bargaining chip, then Facebook and Twitter copy those new features. In this scenario, they leverage their user base and don’t have to waste resources on something as unprofitable as being creative.

But there is another side of the coin. You also have the chance to be part of the prosperous market. By using functionalities that reminds classic social media features (likes, feeds), you can improve the user experience and reduce cognitive overhead when learning about the new app and site.

In the previous article, we’ve created a movie search engine page and add content recommendations to it. Since we used a pre-made dataset with user ratings of movies, the recommendations are static.

In this part, I’ll show you how to breathe some life into your site and give users the ability to co-create it. Using Pipeless, we’ll add like/dislike buttons and a simple activity feed for each video.

🦹‍♀️ Fake websites: How To Detect Phishing

Fischerbach — Wed, 21 Jul 2021 20:11:52 +0000

Phishing is a type of social engineering attack, in which criminals using fake websites to obtain a victim’s sensitive information such as login credentials and credit card details. The phishing websites, emails and apps disguise themselves as trustworthy by making them visually almost indistinguishable from the real ones. The criminals spend a lot of time making their sites so similar to real ones that even experienced users if they will not conscious enough, can be tricked into thinking they are on a legitimate site. The user, convinced that they’ve visited the original site, enters the password, but instead of going to the original publisher, it goes to criminals who can use it for malicious purposes.

The damage done by cybercriminals can be significant and costly, especially if they gain access to the victim’s electronic banking account. Therefore, it is important to prevent this type of attack and detect threats as early as possible. Modern browsers and operating systems have built-in mechanisms to defend users.

These are usually based on lists of known phishing sites. For example, Firefox Phishing and Malware Protection works by checking the sites that you visit against lists of reported phishing, unwanted software and malware sites.

There is also extensive literature available on using scraped page content, IP information or other HTTP properties and processing those to create machine learning models.

In this article, we will present an approach based on screenshots of suspicious sites. By doing so, we will prepare a mechanism that is versatile and resistant to code obfuscation techniques that make crawling difficult. We will create a machine learning model that resembles a real person approach to detecting fraudulent websites by visual inspection.

Detecting fraudulent website traffic using IP geolocation and proxy database

Fischerbach — Wed, 21 Jul 2021 20:09:57 +0000

When our website or web application suddenly receives visits from locations outside the average customer base, or registered users provide data that has a pattern, it may mean that we have been targeted by fraudulent traffic. Detecting this kind of activities is important for many reasons. In the online advertising industry, fraudulent traffic causes additional costs for every market participants. Publishers have to pay for infrastructure used to service. Advertisers pay for traffic that has no value. Other examples are payments processors, all sorts of contests, betting and online casinos.

Because of this, there is a need for sophisticated fraud detection systems. Detecting and preventing traffic fraud to maximize profits and minimizing operational costs is very challenging for publishers.

In this article, I show you how to detect suspicious visits to your website. We will check if IP geolocation and other IP-related characteristics could differentiate good and bad traffic. In the end, we will build rules that help automate the process of fraud detection.

How to create automatic data report in multiple languages

Fischerbach — Wed, 21 Jul 2021 20:08:54 +0000

Once in a while as a data scientist, your job may be to produce a report that you could email to stakeholders or share through the intranet. Word documents may seem a bit old school, but there are still cases when using them is the shortest route to this goal. Whenever automation is discussed, Python is a tool of choice. Creating an automated report using it is a rather standard skill for a data scientist.

But everything’s all fun and games until other languages show up.

In theory, preparing another language version does not seem complicated. After all, it is enough to translate individual labels and descriptions into another language and then hardcode them in the next version of the script. In practice, this simple approach is time-consuming and error-prone, especially when there is a constant need to modify some messages. Not to mention the difficulty of working with non-technical translators using this method.

This article shows how to save time by translating the Python-generated data report by using Gettext and Localazy. I’ll show you how to extract messages from the source code (Gettext), store them in separate files and how to make them available in a collaborative translation tool (Localazy). Also, you will learn how to deal with difficulties in translating f-strings.

How to Forecast Website Traffic

Fischerbach — Wed, 21 Jul 2021 20:06:49 +0000

Data on social phenomena can fluctuate significantly, especially in the internet age. New trends, memes and socio-political movements come and go. This is reflected in internet traffic. Websites number of visits shows impulsive changes that overlap with long-term trends and seasonal patterns.

In this article, I show you how to forecast time series that is quite unpredictable by its nature. You will learn how to use weather data to predict human activity, specifically online. I will show you how to improve your predictions using the domain knowledge of the target variable. We will briefly discuss feature engineering and the evaluation of models. Finally, we develop a web app that trains and tests several predictive models and evaluates them.

How I Built Ad Fraud Detection Dashboard

Fischerbach — Wed, 21 Jul 2021 20:05:30 +0000

Online advertising is still a way to monetise millions of websites. So it is not surprising that with the growth of online advertising, there is a stronger temptation to defraud advertisers’ money by fake traffic. Click farms can generate massive amounts of worthless traffic and ad impressions, by automatically clicking on websites and apps in large numbers.

The technology needed to create a farm of clicking bots is cheap and available. In one of the simplest models, simply use a cloud computing service such as AWS or GCP, which give you access to a multitude of IP addresses and servers.

Ad networks are trying to combat this problem and penalize dishonest website owners. Knowing this, competitors or pranksters can redirect fake traffic to the victim’s website, causing penalties from the ad network, the threat of lost revenue and additional costs.

In this article, I will show you how to build a fake traffic alert system for ad fraud detection. We will create an engine that, based on server logs and a database of IP addresses, will assess the quality of the traffic that the campaign delivers. Finally, we will verify the performance of our system by commissioning a real campaign and assessing whether the traffic from it was legitimate.