Data Management | Rulex https://www.rulex.ai The platform for smart data management Tue, 04 Feb 2025 08:42:16 +0000 en-US hourly 1 https://wordpress.org/?v=6.8 https://www.rulex.ai/wp-content/uploads/2024/05/cropped-favicon_rulex_white-32x32.png Data Management | Rulex https://www.rulex.ai 32 32 The Data Governance-Security Connection: Protecting Your Business from the Inside Out https://www.rulex.ai/the-data-governance-security-connection-protecting-your-business-from-the-inside-out/ Thu, 21 Nov 2024 08:00:14 +0000 https://www.rulex.ai/?p=247481

In today’s digital economy, data is the driving force behind innovation, helping us make smarter decisions and stay ahead of the competition. Yet, data can easily be compromised, leading to costly financial setbacks and lasting reputational damage.

That’s why customers and partners are more cautions about who they trust with their sensitive information. For businesses, it’s no longer enough to simply handle data – they need to prove they can keep it safe. This shift has transformed data governance and data security from ‘nice-to-haves’ to essential pillars of business operations.

table of contents

  1. Data governance VS data security
  2. The 6 pillars of data governance and security
  3. Build lasting customer trust
Average cost to mitigate a data breach, per incident

Source: Washington Post – Cyber threats, real-world consequences

Data governance VS data security: what’s the difference, and why you need both?

Terms like data governance and data security are often used interchangeably, but while they work hand in hand, each plays a unique role in a company’s data strategy.

Data governance is all about setting up internal policies, procedures, and frameworks that define who owns the data, who can access it, and how it’s used. This keeps data organized, consistent, and reliable, helping businesses maintain control over their most important information and prevent employee misuse or accidental mishaps.

A strong data governance structure also opens the door to data democratization, giving users broader access to data while ensuring compliance with established standards. For instance, systems like data mesh break down master data into manageable units, which can be widely accessible to the people who need them, while modifications remain in the hands of a few who have full ownership.

Data security, on the other hand, focuses on protecting data from external threats, both when it’s stored and when it’s exchanged. Techniques such as encryption come into play here, scrambling sensitive information into unreadable code to safeguard it from unauthorized access.

But here’s the thing: without proper governance, data security is like locking your doors without knowing who holds the keys.

So, how can companies make sure their governance and security framework is up to par?

Data governance VS data security: what’s the difference, and why you need both?

The 6 pillars of data governance and security

There are software solutions that can provide companies with the highest standards of security and encryption at every stage of the data lifecycle, while fostering collaboration between teams.

Rulex Platform is designed to meet these critical needs, supporting the creation of a strong, reliable data governance and security framework through six main capabilities:

  1. Data catalogs. Rulex Platform supports data mesh systems, facilitating the creation of sub-catalogs within the user’s preferred cloud environment and enabling resources to be accessed via a shareable yet encrypted username and password.
  2. Clear data ownership. Rulex Platform provides granular control over roles and permissions, which can be assigned to individual users or groups. This means users can decide exactly who gets to see, execute, or delete specific resources, preventing any unauthorized or accidental mishaps.
  3. Policy monitoring. Rulex Platform automatically logs all access to and operations performed within the software. Modifications to the settings and preference files are also logged and encrypted to prevent external alteration.
  4. Event logs. Rulex Platform supports security information and event management (SIEM) technology for log event collection and real-time analysis of security alerts, simplifying compliance tracking and prioritizing incident response efforts.
  5. Advanced encryption. Rulex Platform uses the latest and most advanced TLS 1.3 protocol and AES-256-GCM encryption to protect data at rest and in motion. Users can choose to have encryption keys generated automatically or provide their own, giving the flexibility to match specific security needs.
  6. External vault systems integration. Rulex Platform securely stores sensitive configuration data within its environment or through external vault systems, allowing real-time retrieval of credentials and secrets without embedding them in source code, minimizing the risk of exposure.
Resource Permissions - Inherited Permissions

Granular role and permission management via Rulex Platform’s interface.

Rulex Platform is also ISO 27001 certified, aligning with globally recognized standards for information security management.

Build lasting customer trust

In an era where data breaches make headlines, implementing a strong data governance and security framework has become a business necessity.

Define custom roles and permissions, keeping an eye on all access and changes, and lock down your data with top-notch security and encryption. Request a 30-day Rulex Platform free trial now.

Securely manage your data down to the finest detail with Rulex Platform

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Rulex Platform
]]> Weeding the Data Garden: how Rulex Platform Cultivates Quality https://www.rulex.ai/weeding-the-data-garden-how-rulex-platform-cultivates-quality/ Tue, 04 Jun 2024 07:00:09 +0000 https://www.rulex.ai/?p=243969

Whether it’s an out-of-range value or an incorrect format, the quality of data is fundamental to any data-reliant process and significantly impacts the results, despite often being overlooked. Imagine an enterprise which decides to undergo a large end-to-end business transformation program, where the final aim is to switch to the newest APS featuring so many fancy capabilities. If the data provided to that software is not consistent and accurate, the results will be adversely impacted.

table of contents

  1. Unmask inconsistency
  2. Ignite your rules
  3. Sharpen your rules
  4. Let your data bloom

So, we need to monitor quality in order to ensure adequate accuracy; and to monitor quality we need to… define what Data Quality is. In fact this is rather an “umbrella term” to refer to different issues in the data: Accuracy, Completeness, Consistency, Timeliness, Validity and Uniqueness are some Data Quality dimensions. You can find more information (and more dimensions!) by googling around, so here we rather focus on the solution, which, as the problem, is also multi-faceted.

Rulex Platform provides different capabilities and approaches to solve different Data Quality issues in the same way as a gardener uses various tools and practices to uproot the weeds and make his garden bloom.

Weeding the Data Garden: How Rulex Platform Cultivates Quality

When it comes to harmonizing fragmented data, handling missing values and duplicates, and formatting errors or outliers, Rulex Platform can quickly spot and correct the issue.

A typical Rulex flow foresees these cleansing activities as one of the first actions performed on the raw and dirty dataset. Specific tasks are available which make it simple for any citizen developer to cleanse their data, such as:

  • Fill & Clean: which imputes missing data with fixed or dynamic values
  • Data Manager: which spots and dismisses duplicate rows with a single click

And if these are not enough you can leverage various other features such as:

  • An advanced join capability to merge different datasets based, for example, on string similarity
  • Statistical or textual Data Manager functions, which deal with outliers or incorrect formats
  • …and much more!

Albeit the above approaches have proven useful with many basic issues, there are some cases where a data value seems pretty normal and yet hides an inconsistency.

Unmask inconsistency with eXplainable AI

Among all these dimensions, consistency is one of the most difficult to deal with. A target attribute is considered “consistent” if it changes in accordance with its related attributes; i.e., its values change consistently when the context changes.

The table below illustrates an example of inconsistency (guess why!):

Name
Age
Married
John
28
Yes
Mike
32
No
Paul
5
Yes
Brenda
54
Yes

Also, sometimes you know that a subset of your data is inconsistent, but you don’t have the proper rules to correct it.

Or you have some basic rules, but there are so many exceptions that the final correct values can hardly be identified.

Rulex approaches all the above scenarios with a disruptive solution called Robotic Data Corrections (RDC), which seamlessly provides correction proposals to inconsistent data.

Behind the magic there is a proprietary eXplainable AI algorithm called Logic Learning Machine, capable of inferring a ruleset according to which proposals are devised. With this approach, the user simply accepts or rejects recommendations according to their domain knowledge. The algorithm integrates this new knowledge into successive iterations. After four to five iterations, the accuracy is usually close to 99%.

In addition, RDC catches any new issues in data quality associated to material “phasing in”: at a steady state, minimum effort is required to attain the highest levels of accuracy.

But as we mentioned, the realm of Data Quality is complex and the issue types are diverse: sometimes dependencies from driving attributes involve mathematical formulations, or sometimes even if you do have a settled ruleset, it is not easy to update it. Or maybe the dependency between rules is too complex to manage.

Luckily, the realm of the solutions provided by Rulex is also diverse.

Ignite your rules with the Rule Engine

Rulex provides a task which allows any citizen developer to write their rules with a simple syntax in a simple spreadsheet, import this rule file, and apply the rules to a dataset. This empowering task is called the “Rule Engine”.

The beauty of this approach is that any existing rules can be coded in the task: from the simplest rules to rules involving complex conditions or output values resulting from complex mathematical or logical functions. Also, the whole process of ensuring data quality is completely in the hands of the citizen developer, without needing to resort to skilled expertise to modify the rules or create new ones (definitely shortening the time-to-value).

Finally, our Product Team is working on a solution for those unsure if all the rules are properly configured.

Sharpen your rules with the Rule Enhancer

The Rule Enhancer is an innovative task which refines existing rules: think of it as a tuning tool. It requires a data (sub)set which contains clean and accurate values (the so-called “ground truth”), used to adjust the rules. It also requires some sort of performance criterion (such as the F1 score); as a result, fine-tuned parameters are provided for each rule. If you are interested just hang in there a bit longer: the task will be released in the short!

Sharpen your rules with the Rule Enhancer

Let your data bloom

These multiple approaches together constitute the basis for a 360 degree solution that reaches top accuracy levels, and which can be applied in a comprehensive Data Quality pipeline, so that any kind of issue can be tackled and solved. And what’s more: the implementation can be proficiently managed by any citizen developer who well understands the underlying data.
Rulex Platform provides all the solutions needed to make your knowledge blossom into colourful, accurate data.

Discover Rulex Platform’s data quality solutions

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Rulex Platform
]]> Rule-based Validation: 3 Reasons Why Rulex Does It Better https://www.rulex.ai/rule-based-validation-3-reasons-why-rulex-does-it-better/ Wed, 28 Feb 2024 08:00:34 +0000 https://www.rulex.ai/?p=241265

On September 23, 1999, at 09:00:46 UT, the NASA spacecraft Orbiter lost contact with Earth as it passed behind Mars. The anticipated reconnection, 27 minutes later, never occurred – by that time, the spacecraft had crashed onto the red planet. Subsequent investigations revealed that the incident was caused by commands not being converted from English units to the metric standard.1

On April 8, 2018, a Samsung Securities worker inadvertently entered “shares” instead of the Korean currency “won” due to a keyboard error. This led to the accidental distribution of a “ghost” share worth over 100 billion dollars, ultimately causing a significant decline in Samsung stocks, not to mention a loss of credibility.2

What ties these incidents together? Data quality.

table of contents

  1. Data quality matters
  2. Will a spreadsheet cut it?
  3. Find the expert, spell it out, iterate
  4. Meet the Rule Engine
  5. 3 main benefits of the Rule Engine

Data quality matters

Ensuring data quality involves tasks such as checking if values are within range or have the correct format, and it has been the center of many discussions since the early 1990s.3

Data quality issues may originate in the realm of data, but are certainly not confined to it, significantly impacting business efficiency, incurring higher costs and even jeopardizing the success of projects.4

To tackle the intricacies of data quality problems, organizations of all kinds are constantly looking for effective solutions that can combine both industry expertise and data knowledge.

Will a spreadsheet cut it?

While spreadsheets may suffice for small datasets with simple rules, they prove inadequate as data volume and rule complexity increase. Suppose you have only one or two data sources that you can merge into a small, unified dataset. If the data quality can be assured with simple rules, such as verifying payment amounts within an expected range, a basic spreadsheet formula might suffice.

However, as business requirements grow more intricate, data volume expands, or the need arises to integrate new sources, spreadsheets really start to feel the strain, along with the people trying to use them. Similar to training wheels for a novice rider in a park, a spreadsheet is of little use to an experienced rider navigating a steep downhill track.

a spreadsheet is of little use to an experienced rider navigating a steep downhill track

Find the expert, spell it out, iterate

So with increased complexity, you’ll need a data quality tool that can handle it. Unless you have a very technical background, you’ll also have to get an expert onboard who can implement your rules, such as a Python programmer.

The sort of script your programmer could produce to perform a simple validation check, such as ensuring an amount lies within the 10,000 to 50,000 range, applicable only to projects categorized as “small” or “medium” in size, would look something like this:

  1. import pandas as pd
  3. data = {
  4.     ‘amount’: [12000, 30000, 60000, 15000],
  5.     ‘project’: [‘Small’, ‘Medium’, ‘Large’, ‘Small’]
  6. }
  7. Payments = pd.DataFrame(data)
  8. Payments[‘PaymentStatus’] = ‘INVALID’
  9. mask = ((Payments[‘amount’].between(10000, 50000)) & (Payments[‘project’].isin([‘Small’, ‘Medium’])))
  10. Payments.loc[mask, ‘PaymentStatus’] = ‘VALID’
  11. print(Payments[[‘PaymentStatus’]])

Using an expert to implement the solution is presumably a viable approach, as it allows you to handle volume and complexity. However, it has some important drawbacks:

  • As the execution of any implementation is not within your control, adapting to changes in requirements can be a bit of a journey, involving scheduling meetings to coordinate with programmers and/or tool specialists.
  • Despite investing time in clarifying these changes, there’s always a chance that not every detail will be fully grasped or smoothly executed.
  • And when it comes to integrating new data sources and ensuring they seamlessly align with existing datasets, things can get even more intricate. This can lead to a quick escalation in the effort required, calling for a diverse set of skills to merge and harmonize everything effectively.

The perfect solution would be a tool that can handle high data volumes and varying rule complexities while remaining accessible to a citizen developer.

Meet the Rule Engine

At Rulex, we address data validation challenges with a task called the “Rule Engine“.

This specially designed tool allows users to write business rules in a simple Excel file using an intuitive syntax. The rules can be applied to datasets, and the outputs can be exported to various formats, such as a database, a local file, or via API to an Advanced Planning System.

To assess the validity of our payment data with the Rule Engine, instead of writing a script, it’s sufficient to write a straightforward rule like the following:

  1. IF “amount” > 10000 AND “amount” < 50000 AND “project” in {'Small', 'Medium'} THEN "PaymentStatus" in {'VALID'}

As these rules are written in an external spreadsheet, business users can independently add and modify them, without delving into the intricacies of the workflow, or even needing to know how the software works.

Managing business rules becomes seamless. If the complexity grows, it can be easily addressed thanks to the Rule Engine’s support for formulas within the rule syntax, prioritization of rules (executing fundamental rules first), and the ability to manage rule dependencies.

And if new data sources come into play, they can be imported and merged into the existing flow through a user-friendly drag-and-drop interface.

3 main benefits of the Rule Engine:

  1. SIMPLE: You won’t need to onboard programmers to write complex scripts.
  2. FAST: You can independently modify and test rules and check results in minutes.
  3. FLEXIBLE: You can quickly add new data sources, prioritize rules, and change output, adapting easily to changing needs.

Whether mitigating a space exploration mishap or simply ensuring your business is not losing money, data quality is crucial. The Rule Engine is designed to give citizen developers complete control over the rule management process, enhancing efficiency and contributing to the vigilant maintenance of optimal data quality.

Now is the right time to cast aside those training wheels and confidently navigate your own path along the data trail!

REFERENCES

]]> Optimizing data management: the power of data agility for time, cost, and energy savings https://www.rulex.ai/optimizing-data-management-the-power-of-data-agility-for-time-cost-and-energy-savings/ Mon, 26 Jun 2023 09:54:37 +0000 https://www.rulex.ai/?p=237551

Is my data agile?

Agile data is as boundless as your imagination. It can be aggregated from multiple locations, in different formats, shapes, and sizes, seamlessly merged and shaped into the form you want, is consistent, up-to-date, easy to analyze, and opens up a universe of high-quality optimization and AI forecasting opportunities.

If this is a perfect description of your data, stop reading, and get yourself a glass of cava to celebrate. Kudos to you!

If this description sounds like unicorn utopia, and your data dreams have yet to come true, read on…

Optimizing data management: the power of data agility for time, cost and energy savings

Why is my data wasting time?

Data is such a multi-faceted beast nowadays. It lurks in various forms, from databases to local files, and even sneaks into our email attachments. It can disguise itself as an innocent MS Excel spreadsheet, a tricky table in a PDF, or an elusive SAP table. But the cruellest twist? It never stops changing!

This relentless shape-shifting poses a colossal challenge for companies far and wide. Picture global organizations spanning countries and continents, where each geographic region collects data with its own unique flair – different formats, orders, and even languages. The result? A labyrinth of incompatible data that devours time like trying to pull on a pair of jeans on a sandy, damp beach.

Why is my data wasting money?

In the vast realm of data, there’s a universal truth: garbage in, garbage out. If your data is riddled with inaccuracies, gaping holes, and inconsistencies, it’s a recipe for disaster. Every operation performed on such flawed data becomes a dance of suboptimal outcomes. Optimization becomes a feeble attempt at “making it a bit better-ization,” while AI forecasts stumble in the realm of approximation.

But the story doesn’t end there. The hidden costs of inadequate data lurk beneath the surface, silently draining your finances ($15 million was the average annual financial cost in 2017, according to Gartner’s Data Quality Market Survey). Inaccurate insights then lead to misguided decisions, wasted resources, and missed opportunities. The consequences ripple through every aspect of your operations, chipping away at profitability.

Why is my data stressing me out?

Data should be your ally, not a source of stress and frustration. Imagine a world where agile data effortlessly unveils hidden treasures, allowing you to explore, filter, and query with ease. Business questions are swiftly answered, useful insights and patterns emerge like shooting stars, and data analysis becomes a dream come true for every analyst.

Alas, research reveals a disheartening truth: data scientists devote a staggering 80% of their time to the laborious tasks of data collection, cleaning, and organization, while 76% of them consider this to be the least enjoyable aspect of their work. Valuable time is squandered on frustrating low-value mundane and repetitive tasks, instead of engaging in innovative endeavours, which can be more invigorating than a double-shot of Italian espresso.

Is there a solution to increase data agility?

In the quest for data agility, there is a knight in shining armour: the smart data management platform.

Yet, beware, for not all heroes are forged alike.

So what key attributes should you seek in selecting a platform that genuinely empowers data agility?

First and foremost, start putting time back in your working day by seeking a platform with the power to gather data from every nook and cranny – your platform should be a fearless explorer, collecting data from anywhere it resides.

Ensuring superior quality is paramount when aiming to drive revenue growth, and your chosen platform must rise to the occasion. Seek a solution that enhances data integrity by effectively addressing missing data and outliers, while also leveraging your business rules as a guiding light for validation. Additionally, harness the power of AI to uncover concealed errors lurking in the shadows, bolstering the overall accuracy and reliability of your data.

Finally, to ensure a stress-free experience, it is imperative that your selected platform possesses the innate ability to seamlessly integrate, reshape and transform data. This capability allows you to focus on the enjoyable nerdy aspects, while presenting results through awe-inspiring and interactive dashboards that captivate and inspire.

Rulex Platform ticks all the boxes (and more)

When it comes to conquering the data agility challenges faced by F50 companies, Rulex Platform reigns supreme. We’ve witnessed first-hand the pain caused by incompatible, low-quality, frustratingly unfathomable data, and that’s why we’ve dedicated a lot of our precious time to the art of data agility.

Not only has our platform become a beacon of transformation, saving our clients millions, accelerating their processes, and delivering remarkable results, we’ve also created a user-friendly what-you-see-is-what-you-get haven, welcoming both data nerds and business experts with open arms.

Hidden behind the simplicity of this drag-and-drop interface lies a powerful capability: every operation seamlessly generates optimized code in the background. This extraordinary feature brings forth a multitude of benefits, including CI/CD versioning and collaborative work, automatically generated documentation, swift customization, effortless integration of external scripts, and hassle-free maintenance and debugging.

While we haven’t mastered the art of selling unicorns just yet, rest assured, it’s on our radar.

Are you ready to unlock the full potential of your data?

It’s time to take action

Discover Rulex Platform and witness the power of true data agility.

Start a free 30-day trial and unlock the full potential of your data.

]]> Superior Data Performance: Rulex Outperforms Pandas https://www.rulex.ai/superior-data-performance-rulex-outperforms-pandas/ Wed, 03 May 2023 07:00:53 +0000 https://www.rulex.ai/?p=236699

Anyone who works with data knows how crucial performance is, especially when performing complex data processing and data transformation operations on medium to large datasets.

At Rulex, we understand this need very well, which is why we have devoted a considerable amount of time and effort to ensuring that our software is incredibly fast and efficient.

Processing data fast

Rulex Platform is optimized to handle complex data operations at scale with lightning-fast speed, ensuring that users can process their data quickly and responsively. This feature is especially crucial for companies that rely on near real-time data analytics in their decision-making processes, as slow performance levels can lead to delays and inaccurate information, ultimately impacting services, resources, and business decisions.

Data processing speed: Rulex vs Pandas

To showcase the fast data processing capabilities of Rulex, we have compared it with Pandas, an open-source data manipulation library built on top of the Python programming language.

However, while Pandas is a powerful tool, it can struggle when handling large datasets or complex data operations, leading to slower processing times.

Rulex Platform handles these challenges with speed and efficiency, making it an excellent choice for businesses that need to process data quickly and accurately.

To provide an accurate comparison of Rulex Platform and Pandas, we conducted a series of tests using identical conditions on the same machine and measured the results. We performed ten different operations (group, filter, sort, join, math calculations, concatenation and a sequence of operations) on datasets with the following characteristics: an initial relatively small dataset with 5 million rows of data, a second medium-sized dataset with 15 million rows of data and a final large dataset with 50 million rows of data.

Performance results

Here is a brief summary of our findings to give you an idea of the results we obtained.

SPEED

Our tests show that Rulex Platform was faster than Pandas in 25 out of 30 tests.

Rulex Platform consistently outperformed Pandas across all three datasets.

The difference in data processing speed was particularly pronounced on the largest dataset, containing 50 million rows. In one test, Pandas took 30 minutes to process the data, while the Rulex Platform accomplished the same task in just 26 seconds!

MEMORY USAGE

Rulex Platform outperformed Pandas in terms of memory usage in 28 out of 30 tests.

Our tests revealed that Rulex Platform consistently used less memory than Pandas across all datasets and operations, except in cases where both tools were close to reaching the memory capacity of the computer itself.

In such cases, the memory peaks of both tools were similar, but Rulex Platform demonstrated better performance levels than Pandas.

Rulex Platform Pandas

More Rulex-Panda data performance comparison

If you are interested in learning more about our testing methodology and results, we have provided a detailed description on Rulex Community: Rulex Platform vs Pandas: Performance Comparison.

Feel the speed of Rulex Platform

Interested in trying Rulex Platform straightway? Get a 30-day free trial.

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Matteo Aragone - InfoSec Manager

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InfoSec Manager
Walter Rossi

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Data Scientist
]]> Business rule engine: who rules the rules? https://www.rulex.ai/business-rules-engine-who-rules-the-rules/ Tue, 02 May 2023 06:00:16 +0000 https://www.rulex.ai/?p=236795

Have you received a discount from your favorite clothing brand? Business rules were probably involved in the decision-making process. Often brands set business rules that award discounts every time a certain value is reached by the customer. But who defines and executes rules in a company? Basically, who rules the rules?

What are business rules?

Business rules play a crucial role in companies’ operations and processes, as they guide the everyday decision-making within the business. They express business goals, guidelines, regulations, performance requirements, etc. while automating processes.

A rule can be formulated to indicate a particular course of action to be followed under specific circumstances or to prevent certain actions from happening.

For instance, e-commerce analysts can set business rules to apply customer discounts or for pricing optimization, while financial institutions employ them to improve decision-making for risk management: they suggest to bank clerks whether a loan should be granted or not.

Moreover, business rules streamline operations. They can be set to conditionally process documents and invoices or to route customer service calls.

Business rules keep things going while helping maintain consistency across the organization.

Business rule engines: who rules the rules

Translating activities into concrete business logic is a great deal for companies in terms of efficiency and accuracy, as business rules reduce manual data entry, lowering the risk of potential errors, while automating repetitive tasks.

But who executes business rules, especially in complex environments where multiple constraints are involved?
That’s where business rule engines (BREs) come in.

A business rule engine is a piece of software that runs the rules on the provided business data, and if any condition
matches then it executes the corresponding actions, automatically responding to real-time situations.

Most rule engines, like Rulex Platform, don’t do just that. They also define new rules by using machine learning algorithms, integrating the existing rules provided by business experts.

Heuristic rules vs AI-generated rules

Heuristic rules are those that have been extrapolated from personal experience. Industry experts
define the decision logic after a careful analysis of historical data. They may compare new and old data patterns,
monitor new and real-time data, make assumptions to fill in the gaps, and then come up with a set of business
rules to apply to the business process.

AI-generated rules, on the other hand, are extrapolated by machine learning algorithms starting from the historical data of the business. In Rulex Factory, the heart of Rulex Platform, for example, these types of rules take the form of an if-then expression.

These two different types of rules can be merged together in the decision process, to achieve the best possible outcome.

How to manage business rules in Rulex Factory

Let’s take a look at how Rulex Factory manages business rules.

As business rules often have many dependencies, constraints, and mathematical formulas, Rulex has developed a
simple syntax that enables non-technical users to express these rules in a simple tabular format, such as an MS Excel file. With a simple drag and drop, you can then import the file into Rulex Factory and apply it to your business data.

If you have very simple rules, there is an even quicker way of managing rules. Once you have dragged and dropped
your data onto Rulex Factory’s canvas, just connect a Rule Manager task. This user-friendly task enables you to apply any pre-defined business rules to your data in a simple if-then format.

In the example, we added the business rule that defined which transport to use depending on the weather and working mode:

Weather = Sunny AND Smart Working = No, THEN Transport = Bicycle

There are two conditions, weather and smart working, which define the output, bicycle.

How to create business rules in Rulex Factory

Manually extrapolating the best rules from historical data is not always an easy task. However, specific algorithms
can analyze the data and generate business rules for us.

In Rulex Factory, we use the Logic Learning Machine (LLM), Rulex’s proprietary algorithm that produces clear and understandable if-then rules.

No technical expertise is required, and business users can create rules using the LLM with ease and confidence.

In the example, we connected the LLM task to our data, selected the attributes we want to use as input (e.g. weather conditions and working mode) and those that represent the output of the analysis (e.g. suggested method of transport), and computed the flow. By connecting a Rule Manager task to the LLM task, we can then easily check the AI-generated rules.

All the benefits of business rules engines

Rulex Factory is used every day by large-scale supply chains and financial institutions, and these are some of the main advantages pointed out by our clients:

  • Improved efficiency:
    Programming business rules into workflows saves lots of time by automating tasks.
  • Reduced complexity:
    Business rules are represented in simplified formats (if-then) that do not require coding skills.
  • Increased consistency:
    Updates to business rules can be immediately applied without modifying the software code.
  • Enhanced compliance:
    It makes it easy for businesses to comply with industry regulations and GDPR.
  • Boost business agility:
    Enabling faster changes makes it possible to react more quickly to new opportunities.

Handle complex scenarios with Rulex Rule Engine

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Rulex Platform

]]> Data Management - Rulex nonadult Why Rulex Lite? An interview with Rulex’s CEO, Marco Muselli https://www.rulex.ai/why-rulex-lite-an-interview-with-marco-muselli/ Thu, 02 Mar 2023 08:00:29 +0000 https://www.rulex.ai/?p=236053

We asked the CEO of Rulex, Marco Muselli, to explain why he has decided to launch an entry-level version of Rulex’s data management system: Rulex Lite.

Why has Rulex started selling an entry-level version of its software?

As we speak, Rulex Platform is being used by many large enterprises around the world to optimize and digitalize their business processes, which is great news for us. But it has always been my ambition to make this powerful technology accessible to anyone who handles data, and needs to perform simple everyday operations, but does not have the programming skills to go beyond Excel spreadsheets.

Rulex Factory Lite Annual

How have you managed to lower costs so significantly?

We basically removed or reduced the software capabilities that are really only essential for large enterprises and focused on maintaining what is important for personal users and small businesses. So this version doesn’t have the features for working in large groups, and also has a data limit of 10 million cells, which is still more than sufficient for small companies and individuals, and way beyond what Excel can handle. These changes meant we could bring costs right down and offer a very affordable version of the software.

Who do you think would be interested?

There are many small companies and business owners who simply cannot afford expensive enterprise solutions, but would really benefit from this useful technology, and a low-cost license gives them a chance to greatly improve how they handle and get value from their data. Another group that comes to mind is students, and generally the world of academia, especially in non-scientific faculties, such as economics and marketing. This group of people may not have the technical knowledge to build custom solutions, but nonetheless need to handle large amounts of data and build data analysis logic.

How can people learn how to use Rulex Platform?

The software itself is a graphical tool, which means you just drag and drop data files and tasks onto a canvas, where you then work on the data in spreadsheets, so it’s very intuitive. But you can also build pretty complex business logic through its available tasks, so you’ll need to learn a little about how to interact with the software to make the most out of its capabilities. We’ve tried to make this as simple as possible, so although you’ll find initial help in walkthroughs and technical documentation, we’ve also built a strong community, where you can download sample workflows, take free courses, ask for ideas in discussion forums, watch explanatory videos etc. We try to guide new users as much as possible, and don’t take any tech skills for granted.

How can people buy this entry-level license?

People can pick it up directly with a credit card through the Rulex Community store, without the hassle of having to speak to sales reps or fill in endless forms. There is a monthly and annual subscription, so if you don’t want to commit, you can try it out for a few months and see how it goes.

Is there still a free trial?

Absolutely, there is a 30-day free trial to try it out. If you get on well with the software, you can subscribe for a month at a time, with the option of switching to an annual subscription, and saving yourself another 20%, when you’re really appreciating the benefits. With a cost of €95 per month, I feel I’ve realized my ambition to make it accessible to everyone.

]]> Smarten up your everyday data management https://www.rulex.ai/smarten-up-your-everyday-data-management/ Fri, 10 Feb 2023 09:00:23 +0000 https://www.rulex.ai/?p=235770

Gathering and merging data from multiple sources and formats can be a huge initial hurdle to overcome for many businesses. Importing data into Rulex Platform really is as simple as dragging and dropping a task.

The first step in any data management process is gathering your data. But when you start looking at what you have, you’ll soon find that it’s pretty messy and disorganized. You may have transactional data on an SAP database, numerical data stored in MS Excel files on a SharePoint repository, and text files saved locally.

To complicate matters further, each dataset is likely to be structured according to its purpose. Transactional data may be based on the Order ID, customer service data on the Customer ID, and product data naturally on the Product ID.

So, how can we merge all these sources, and make any sense of it all?

Getting off the starting block to data collection

Getting started with a data management plan is always the hardest part. It may leave businesses, big or small, on the starting block, wondering what to do first.

In Rulex we understand your pain, so we’ve made sure that Rulex Platform has all the tools you need to be the first off the block.

Let’s go through the key actions data scientists and business analysts perform when importing and merging data on Rulex Platform.

Importing data from different sources

It really is as simple as dragging and dropping a task and selecting the source where your data are stored.

Rulex Platform is all WYSIWYG, so while you change options in the task, you get to see a preview of what data you are about to import, and how.

So, what databases are supported? Pretty much all the commonly used databases available on the market. Including SQL Server, MySQL, Postgres, Teradata, Hive, Impala, Spark, Azure Synapse, DOMO, Snowflakes, Oracle, SAP 4 HANA, and IBM DB2 series. And the list keeps growing.

Once you have set up the connection parameters for your database or file system, you can save them, and even set permissions to share them with other users.

Importing data from different sources

And if your data are in the cloud? No problem. Rulex Platform supports AWS S3, Microsoft SharePoint, FTP/S and HTTP/S servers, Hadoop HDFS filesystems, Share drives, Azure Files, BLOB Storage, and many more.

Blending data with different file formats

Data can be imported from practically anywhere, but what about the format? Everyone knows that each format has its own structure and requirements.

To speed up the process, there are separate tasks for the main data types, such as MS Excel, text files (csv, tab, txt), XML, JSON.

Once imported, Rulex Platform automatically converts the file into a single table format, even working out the data type of each column. Whether your original data was in MS Excel, CSV, XML or an SAP table, the imported results will all look the same in Rulex. So it’s then really easy to quickly reshape these tables, and blend them into a single spreadsheet.

Importing data with different file formats

If you’d like to know more about table transformation, check out our article on Rulex Community: Could you please reshape my table?

Harmonizing data

Summing up what we’ve seen so far, Rulex Platform not only allows you to import multiple data formats, from multiple sources, but also merge all these files into a single spreadsheet, providing you with a user-friendly data view in just a few easy steps, so you can start getting the answers you were looking for.

Handling really big datasets

As your business grows, the data you have at your disposal does too. To the point where it is difficult to handle. Excel files may grow to such as extent that Excel itself has problems opening them, and even simple data-prep operations become excruciatingly slow.

Thus, questions start arising. Is there a risk in merging all our data into a single dataset? Will it get so big that even sorting columns will become painfully slow?

The simple answer is: no. Rulex Platform can handle vast amounts of data extremely quickly. For example, it can sort 5 million rows of data in 2.2 seconds. Impressive.

Exporting data in whatever format

Once your data have been imported and elaborated, you can export the results how and where you want. Just drag an export task onto the canvas, and select the format you want and the destination, which can even be via email to a list of recipients.

Importing data with different file formats

Using REST APIs to import/export data

Rulex Platform has a REST API that allows you to programmatically import data into the platform. This method can be useful if you want to automate the data import process or if you want to integrate Rulex with other systems.

Ready to import and combine data on Rulex Platform?

You can download a free trial from Rulex Community, where you’ll also find discussion forums, articles, interactive courses, sample flows, and videos to get you off to a flying start with your data.

And just to answer your last question – is Rulex Platform too expensive for a small business or personal user? The answer is no, with a starting price of €95 / month Rulex Platform is very accessible.

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