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Gartner predicts that by 2023, over 50% of medium to large enterprises will have adopted a Low-code/No-code application as part of their platform development.
The proliferation of Low-code/No-code tooling can be partially attributed to the COVID-19 pandemic, which has put pressure on businesses around the world to rapidly implement digital solutions. However, adoption of these tools — while indeed accelerated by the pandemic — would have occurred either way.
Even before the pandemic, the largest, richest companies had already formed an oligopsony around the best tech talent and most advanced development tools. Low-Code/No-code, therefore, is an attractive solution for small and mid-sized organizations to level the playing field, and it does so by giving these smaller players the power to do more with their existing resources.
While these benefits are often realized in the short term, the long-term effect of these tools is often shockingly different. The promise of faster and cheaper delivery is the catch — or lure — inside this organizational mousetrap, whereas backlogs, vendor contracts, technical debts, and constant updates are the hammer.
So, what exactly is the No-Code trap, and how can we avoid it?

What is a No-Code Tool?

First, let’s make sure we clear up any confusion regarding naming. So far I have referred Low-Code and No-Code as if they were one term. It’s certainly easy to confuse them — even large analyst firms seem to have a hard time differentiating between the two — and in the broader context of this article, both can lead to the same set of development pitfalls.
Under the magnifying glass, however, there are lots of small details and capabilities that differentiate Low-code and No-code solutions. Most of them aren’t apparent at the UI level, leading to much of the confusion between where the two come from.
In this section, I will spend a little bit of time exploring the important differences between those two, but only to show that when it comes to the central premise of this article they are virtually equivalent.

Low-Code vs. No-Code Tools

The goal behind Low-Code is to minimize the amount of coding necessary for complex tasks through a visual interface (such as Drag ‘N’ Drop) that integrates existing blocks of code into a workflow.
Skilled professionals have the potential to work smarter and faster with Low-Code tools because repetitive coding or duplicating work is streamlined. Through this, they can spend less time on the 80% of work that builds the foundation and focuses more on optimizing the 20% that makes it different. It, therefore, takes on the role of an entry-level employee doing the grunt work for more senior developers/engineers.
No-Code has a very similar look and feel to Low-Code, but is different in one very important dimension. Where Low-Code is meant to optimize the productivity of developers or engineers that already know how to code (even if just a little), No-Code is built for business and product managers that may not know any actual programming languages. It is meant to equip non-technical workers with the tools they need to create applications without formal development training.
No-Code applications need to be self-contained and everything the No-Code vendor thinks the user may need is already built into the tool.
As a result, No-Code applications create a lot of restrictions for the long-term in exchange for quick results in the short-term. This is a great example of a ‘deliberate-prudent’ scenario in the context of the Technical Debt Quadrant, but more on this later.

Advantages of No-Code Solutions

The appeal of both Low-Code and No-Code is pretty obvious. By removing code organizations can remove those that write it — developers — because they are expensive, in short supply, and fundamentally don’t produce things quickly.
The benefits of these two forms of applications in their best forms can be pretty substantial:
  • Resources: Human Capital is becoming increasingly scarce — and therefore expensive. This can stop a lot of ambitious projects dead in their tracks. Low-Code and No-Code tools minimize the amount of specialized technical skills needed to get an application of the ground, which means things can get done more quickly and at a lower cost.
  • Low Risk/High ROISecurity processes, data integrations, and cross-platform support are all built into Low-Code and No-Code tools, meaning less risk and more time to focus on your business goals.
  • Moving to Production: Similarly, for both types of tools a single click is all it takes to send or deploy a model or application you built to production.
Looking at these advantages, it is no wonder that both Low-Code and No-Code have been taking industries by storm recently. While being distinctly different in terms of users, they serve the same goal — that is to say, faster, safer and cheaper deployment. Given these similarities, both terms will be grouped together under the ‘No-Code’ term for the rest of this article unless otherwise specified.

List of No-Code Data Tools

So far, we have covered the applications of No-Code in a very general way, but for the rest of this article, I would like to focus on data modeling. No-Code tools are prevalent in software development, but have also, in particular, started to take hold in this space, and some applications even claim to be an alternative to SQL and other querying languages (crazy, right?!). My reasons for focusing on this are two-fold: 
Firstly, there is a lot of existing analysis around this problem for software development and very little for data modeling. Secondly, this is also the area in which I have the most expertise.
Now let’s take a look at some of the vendors that provide No-Code solutions in this space. These in no way constitute a complete list and are, for the most part, not exclusively built for data modeling. 

1. No-Code Data Modeling in Power BI

Power BI was created by Microsoft and aims to provide interactive visualizations and business intelligence capabilities to all types of business users. Their simple interface is meant to allow end-users to create their own reports and dashboards through a number of features, including data mapping, transformation, and visualization through dashboards. Power BI does support some R coding capabilities for visualization, but when it comes to data modeling, it is a true No-Code tool.

2. Alteryx as a Low-Code Alternative

Alteryx is meant to make advanced analytics accessible to any data worker. To achieve this, it offers several data analytics solutions. Alteryx specializes in self-service analytics with an intuitive UI. Their offerings can be used as Extract, Transform, Load (ETL) Tools within their own framework. Alteryx allows data workers to organize their data pipelines through their custom features and SQL code blocks. As such, they are easily identified as a Low-Code solution.

3. Is Tableau a No-Code Data Modeling Solution?

Tableau is a visual analytics platform and a direct competitor to Power BI. They were recently acquired by Salesforce which is now hoping to ‘transform the way we use data to solve problems—empowering people and organizations to make the most of their data.’ It is also a pretty obvious No-Code platform that is supposed to appeal to all types of end-users. As of now, it offers fewer tools for data modeling than Power BI, but that is likely to change in the future.

4. Looker is a No-Code Alternative to SQL

Looker is a business intelligence software and big data analytics platform that promises to help you explore, analyze, and share real-time business analytics easily. Very much in line with Tableau and Power BI, it aims to make non-technical end-users proficient in a variety of data tasks such as transformation, modeling, and visualization.

You might be wondering why I am including so many BI/Visualization platforms when talking about potential alternatives to SQL. After all, these tools are only set up to address an organization’s reporting needs, which constitute only one of the use cases for data queries and SQL. This is certainly a valid point, so allow me to clarify my reasoning a bit more.

While it is true that reporting is only one of many potential uses for SQL, it is nevertheless an extremely important one. There is a good reason why there are so many No-Code BI tools in the market—to address heightening demand from enterprises around the world — and therefore, it is worth taking a closer look at their almost inevitable shortcomings.

Source de l’article sur DZONE

Le climat économique et social actuel a mis les entreprises de toutes tailles face à des défis inédits. Notre époque n’avait encore jamais connu de tels chamboulements, à la fois internes et externes. Les directeurs et services financiers, qui s’efforcent de bien gouverner leur entreprise, vivent sans doute les moments les plus difficiles de leur carrière.

À l’heure actuelle, le directeur financier et surtout l’équipe de planification et d’analyse financières doivent continuer d’avancer malgré de nombreuses incertitudes, notamment :

  • l’impact des perturbations des canaux de ventes sur le chiffre d’affaires
  • la gestion du flux de trésorerie et des liquidités
  • la gestion des dépenses et la maîtrise des coûts
  • les projections financières optimistes et les conseils basés sur des suppositions floues

Incertitudes et choix à faire

Pour le service de planification et d’analyse financières, ce ne sont pas des questions isolées, mais tout un ensemble de problèmes et de doutes qu’il faut gérer de manière globale. Faut-il puiser dans une ligne de crédit pour préserver la fluidité du fonds de roulement ? Le flux de trésorerie et les liquidités actuels permettront-ils de couvrir les dépenses à court terme ainsi que les initiatives de capital actuelles et à venir ? Peut-on bénéficier des programmes gouvernementaux d’aide salariale ? Que dire aux actionnaires sur les prévisions du solde de l’année ? Existe-t-il des moyens d’aider nos clients à réussir ?

Ces questions se posent aux services financiers, mais aussi à l’ensemble de l’entreprise, dont les différentes équipes se penchent sur les budgets et les tactiques envisageables.

  • Les programmes actuels tiennent-ils compte du marketing ?
  • La chaîne logistique est-elle confrontée à des disruptions ?
  • Quelles sont les conséquences pour la planification de la demande
  • Quelles sont les suggestions des RH concernant les niveaux d’effectifs actuels, et quels effets auront-elles sur les résultats ?

Il faut regrouper tous ces budgets et modèles individuels en une vue unique pour pouvoir comprendre les interdépendances.

Planification d’entreprise collaborative pour éliminer les silos

Un paradigme de planification moderne permettrait de résoudre facilement ces problèmes : la planification d’entreprise collaborative. Elle consiste entre autres à éliminer les silos, et ainsi à relier instantanément toutes sortes de plans. Les finances disposent donc d’un aperçu réel de la santé financière actuelle pour ne prodiguer que les conseils les plus avisés. Par exemple, elles peuvent évaluer l’impact d’un plan commercial sur les campagnes marketing, ou relier un processus S&OP (ventes et opérations) rapproché à un plan financier. Un analyste peut déterminer quel plan d’effectifs pourrait impacter la productivité des collaborateurs et la trésorerie.

Les finances doivent aussi pouvoir prendre des décisions rapides. Grâce à la planification d’entreprise collaborative, le service financier n’est pas tenu de suivre les plans établis. Aujourd’hui, on ne peut plus travailler dans un environnement où les plus mauvais services financiers repoussent les décisions parce qu’ils utilisent des feuilles de calcul et outils de planification obsolètes. Si au contraire ils disposent des technologies adéquates, ils pourront instantanément simuler l’impact de plusieurs scénarios. Les outils d’analyse modernes associés aux outils d’analyse prédictive et au Machine Learning leur permettront de suivre les recommandations pour obtenir les meilleurs résultats. Quant aux tableaux de bord et à la visualisation intégrée, ils offrent aux utilisateurs finaux un reporting en temps réel et une expérience esthétiquement agréable avec un risque d’erreur minimal, contrairement aux feuilles de calcul.

Une discussion instantanée pour une prise de décision rapide

Enfin, la plupart des organisations, y compris les services financiers, ont étendu leur capacité de travail à l’espace virtuel ; elles ne sont plus limitées par les murs de l’entreprise. La planification d’entreprise collaborative encourage la discussion instantanée pendant la planification et la prévision. Les problèmes géopolitiques ont eu des répercussions extraordinaires sur les prix des marchandises. Une situation qui, tout comme les problèmes liés à la pandémie, nécessite une collaboration et un consensus immédiats. Les décisions doivent être prises sans délai, sans le soutien des réunions, messages vocaux ou fils d’e-mails.

Avec la planification d’entreprise collaborative, les services financiers peuvent guider leur entreprise pour l’aider à obtenir les meilleurs résultats et à continuer d’avancer dans le bon sens malgré les difficultés du moment. La planification d’entreprise collaborative permet aux finances de comprendre tous les aspects de leur entreprise, de recommander et d’évaluer divers scénarios, de prendre les bonnes décisions, et de se positionner comme les véritables leaders de l’entreprise.

Pour en savoir plus, lisez ce rapport de Ventana Research intitulé « Planification d’entreprise collaborative : Améliorer la valeur opérationnelle de la planification et de la budgétisation à l’échelle de l’entreprise ».

À propos de Pras Chatterjee

Pras Chatterjee est directeur marketing produits principal pour la planification et l’analyse chez SAP, en particulier pour les solutions SAP Analytics Cloud et SAP Business Planning and Consolidation. Avant de rejoindre le service Marketing produits, Pras était directeur du cabinet SAP EPM et responsable des services SAP Business Analytics en Amérique du Nord. Il a également été architecte de solutions pour SAP, spécialisé dans la planification et les consolidations dans le monde entier. Comptable agréé, Pras a travaillé au service financier de diverses sociétés de logiciels, dont plusieurs entreprises du Fortune 500.

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Source de l’article sur sap.com