Editorial archive of Creangel. The references, figures and conditions correspond to the original publication.
Every day the needs of companies to improve methods of processing and gathering information processes, the mechanisms for storing and analysing data from activities or operations are more demanding. What companies are looking for is that these actions help optimize the performance of each of the areas and are the goals of the development and innovation department. It is from this need to control the visualization of information and decision-making based on strategic data, that a few years ago the term Business Intelligence is heard very often and in companies it is already an acquired necessity.
At Creangel we stand out for the creation of tools based on real needs of companies and disruptive optimizations based on the most advanced technology. Our experience of more than 18 years gives us a strategic look, which only seeks to give companies everything they need to create an integrated visualization of the company and in a simple and friendly way help in decision-making. To achieve this, we focus on changing the way things are done and on improving processes.
In order to understand the impact of Lakehouse on our day-to-day life, I will tell you in a simple way how it works and how it improves quality in analytics processes and hence all business intelligence (BI) activities from Creangel's designed tool.
All information analysis processes are based on one or more sources of information, unprocessed data are collected from the business activity. Data is processed and stored in data warehouses. Once stored, users can access the data, which starts the analysis process to answer business questions. This information in most companies, is part of their transactional system and it is necessary to take care of the performance of such systems so that search actions do not slow down these tools that are necessary for the running of the Core of the companies.
Here traditional analytics systems have two options; the first is effectively to take care of the operation of the company's transactional tools and what they do is to capture the information in several times and of that information (which is worth clarifying will never really be updated), previews some tables that can be used by analysts, knowing that these requests for information can last hours and even days in being delivered. And on the other hand there is not taking all the information but an average of this (a piece), and if companies want the information in real time it will always be impacting the transactional slowing down the daily shares of the company.
In addition, traditional data visualization options for analytics are not designed or prepared for immense volumes of information, giving as a subsequent activity the need to divide information in order to manage it and repeat it several times the process and this is an action completely opposed to the optimization of processes that is the goal so companies turn their eyes towards business intelligence. That is, what companies now use to visualize information and make decisions that optimize and improve the company's processes must be improved because it is based on repetitive actions and reprocesses.
Hence Creangel's need to design a tool capable of handling large volumes of information, in real time, with all the data (not just a piece), without impacting the transactional and the latter, but no less important, easily accessible on operational and cost issues.
That's how our tool works. To start IFINDIT for Analytics works under a type of database that allows to maintain a history of the state through the time of different sensors and measurements, the time and nature of time in each of the data is fundamental to be able to do our job well, since, being based on a Lakehouse, it is a high performance real-time analysis database where the search part of these measurements. The innovative and heterodox of our tool and that really makes the difference is based on the following 3 components:
The first is the coordinated processing that refers to having different warehouses (nodes) independently, the tool has the possibility to work with all the warehouses you need depending on the size of the information, while traditional tools do it only with a warehouse. For example, it has a master warehouse that controls all actions towards the server, has warehouses that distribute queries, has data warehouses and is in the ability to create necessary warehouses, thousands of individual warehouses if you need them to answer queries in record times. That is, if we move this way of working to a coffee plantation, it is not the same result of a single collector to 200 collectors doing the same activity at the same time. By the end of the day the 200 collectors will have brought more coffee to the threshing machine far above the work of a single collector that will also last much longer to harvest the entire harvest. This also allows us to increase the number of users doing searches because the search is done horizontally across all warehouses and not vertically by a single warehouse, which also impacts the cost of traditional tools and our tool that is much more accessible, because it is not by the number of searches or by users, you can search millions of times, and you can have users everywhere and the price will be the same.
The second is the hybrid architecture that refers to that we have local components and spaced storage, this is basically separate storage and processing. Here we can use deep storage to redistribute the workload and that does not collapse, the warehouses to which we refer above (nodes) have workloads distributed automatically which leads to no dead time in activities or idle time and manual work, and is one of the features that most like the traditional tools of the competition. An example with daily life is the purpose of a shift assignor such as that used in customer service companies, users arrive, take the turn and are assigned to an advisor, this ensures that advisers attend in order of arrival, depending on the need of users and in the shortest possible time optimizing the time of consultants in an organized manner. This is guaranteed by the hybrid architecture of the IFINDIT analytical tool.
And the third is an efficient storage engine. Storage engines are a group of functions closely related to the stored database. This engine is similar to software hidden between the store layers (nodes) of our tool and is used to create, update, edit, view or delete data. If we visualize our stores as your city's library, the efficient storage engine, is the library that keeps the entire catalogue up to date, makes updates, eliminates what is no longer useful, enters new books and allows you to visualize them. As you can see having efficient storage engine is paramount within Creangel's analytics tool.
To end with the features of the analytics tool there is no more friendly option on the market, with less implementation time and easier to adapt than IFINDIT for interactive Dashboards. While with the traditional tools of the competition your developers must be code experts and learn from millions more to adapt them to everyday life, our tool is delivered completely usable, no more code, we make them for you.
The above in architecture and technology issues, if we want to see the results, speed and price, we can say that Creangel's IFINDIT tool offers 3 times above traditional tools, responds 14.3 times faster queries and in operations can do so in the third part of time. And if we talk about price, performance and benefits the IFINDIT tool for analytics is created thinking of the Colombian and Latin American market.
The competition that markets traditional tools bill by query, by search and by user makes it very difficult to size what the real cost of the tool would be in the medium and long term, even in the short term, since costs can rise exponentially abruptly when the company uses the tool and does more daily searches, additional to consulting and trainings of tool management. Unlike the above, the Creangel analytics tool is billed by blocks and ranges of information, so from the very first moment you know the cost of the tool without added values, nor surprise expenses. That is to say, they can perform all the imagined searches and from all the users who need it. We have met in the market with companies that hired the traditional tools of the competition and started with a moderate value in the first month with a small impact of 10% of users and the necessary searches and in the third month they had to suspend the pilot because it exceeded 100 times the initial value, this without even being able to endure all the real need of the company. If we compare the real value of our tool, with the use of traditional tools, this can be 4 times higher, adding the volatility of the dollar price and additional implementation costs.
There are many sources and information systems that companies need to take into account, but they cannot spend months in invasive implementation with incalculable economic values. Investment in the visualization of analytical assertive information should be translated for companies into:
- Cost and time savings to increase productivity in the company
- Meet efficiency goals.
- Discover new ways of business and growth.
- Understand current customer needs and improve their user-friendly services.
- Promotes proper knowledge management within departments by graphically showing data that could go unnoticed
- True decision-making backed by reliable, up-to-date and comprehensive information
Not in one more headache. In conclusion, the operational and cost advantages of a tool completely adapted to the local market, developed 100% by Colombians, is the response to the needs of companies and constant search to stay at the forefront. To ensure that the tools used to optimize processes are not obsolete, avoiding setbacks in them, permanently modifying the way information is accessed and visualized and its participation in decision-making. The answer is on Interactive Creangel Dashboards IFINDIT.
Author: Creangel