Que es business intelligence blog

What is Business Intelligence?

by Business

Business Intelligence is a process enhanced by technology that helps companies improve the way they make decisions; it empowers companies to find answers to business questions with the data they already have in their digital ecosystem. 

It contributes to decisions based on data and not on subjective elements like the personal experience of decision-making leaders.

Keeping in mind this is a process and requires strategy, it is crucial to reach goals. What does this process consist? How many stages does it have? The thorough process goes from data source identification and treatment definition to data consumption of final users. It has these stages:

Data collection

  • Data sources identification, both internal and external, will work as data providers for the business intelligence process.
  • Definition of rules about how frequently data will sync and where.
  • Real-time vs historical data: Decide whether to work with real-time data, historical data, or both. 

Data preparation

Once data is collected, it should be prepared to meet quality and availability criteria. This step includes data integration, data consolidation, and data cleansing. 

Creation of queries: Define what questions your business needs to answer.

Dashboards and reports creation: Select what graphic representations are better to represent data findings. If you want to know more about this, we recommend reading: Tips to create a successful dashboard. 

At this point, you must define roles for users according to their specific needs for data consumption. 

Thinking about it, you will define roles for internal and external users, according to their data consumption needs.

What kind of analysis can be performed by BI tools?

Essentially, there are three kinds of analysis. 

  1. Descriptive analysis. It helps to answer questions like Why did something happen?, Is it going to happen again? This analysis is useful to visualize data on several levels to discover why something happened. 
  2. Predictive analysis. It models future scenarios and the results we might expect from them. It is good to make decisions related to goal achievement, for example, how a new line of products or a new business division, will impact overall sales.    
  3. Prescriptive analysis: It recommends business actions based on data so the decision makers reach their goals.

Business Intelligence for everyone 

In the beginning, business intelligence tools were for C-level executives. But it changed, and now they have evolved in terms of concepts and technologies. This evolution has nurtured an open approach that empowers all business users to make their decisions based on data. This way, not only strategic decisions are made with BI, but also operative ones. 

That is why once everything from the previous point is ready, users will make better decisions. It does not matter if it is about deciding the right time to release a product in the market or when to contact a lead that is more likely to purchase. 

BI is still evolving, allowing more users to become part of the data culture in their workplaces. It helps improving decisions making process, guarantees better decisions, more efficiency, and enhances business opportunities.

What are the benefits of modern business intelligence?

Besides improving the decision-making process in the Company, it offers these advantages. 

  1. It helps to identify the reasons behind results, especially when data volume makes it impossible for a human being to identify such causes. 
  2. It increases organizational efficiency: It delivers integral access to information to business leaders, delivering an overview of their business areas and the Company, making it easy for them to identify synergy opportunities inside the organization. 
  3. It allows saving time in data consulting. Asking for data from the whole digital ecosystem, cuts off time invested in tasks related to data consultation and delivers a complete overview of what is happening in the organization.
  4. Accessing relevant information in real-time. Useful when decisions require current data and not historical to be made
  5. Faster data consumption. Graphic representation options allow efficient data consumption by synthesizing information in a short space and highlighting what matters. 

If you are looking for all benefits of business intelligence for your Company, then we recommend you to know BI4Web. It is a 100% web tool that allows access to all business intelligence benefits from any device, any where, and anytime.  

    Barriers to business intelligence adoption

    Main barriers to business intelligence adoption

    by Business

    Business Intelligence is a widely known concept used for the very first time by Howard Dresner in 1989. Since then, it has been gaining popularity. Currently, most companies are aware of its importance in digital transformation. However, there are still many barriers that stop or slow down adoption.

    Identifying these barriers is crucial because it is the first step to overcoming them.

    In this article, you will find the main barriers to business intelligence adoption and recommendations for overcoming them. They range from selecting the right tool or solution to having a data ecosystem ready for business intelligence challenges.

    Barrier 1. Lack of proper training
    Without training suited for a team, the learning curve will tend to last longer than expected, which can result in employees neglecting the use of the new tools or solutions. In these cases, users go back to using Excel since they are familiar. In other words, users should learn as fast as possible; so frustration does not reach unwanted levels.

    A good piece of advice in this matter is to identify the most common tasks and lead training to solve these works first. This way, your team will stay motivated from the beginning by incorporating the new tool into their daily routine.

    Barrier 2. Data not available or poor quality

    Since data is the raw material for business intelligence, accessing reliable data is crucial. One of the most popular misconceptions about business intelligence might reside in the belief installing a business intelligence tool can solve poor data quality immediately. Something completely false.

    To take down this barrier is critical to understand that the implementation of a solution must include recognition of databases, data sources, and data flows; and identify problems derivated from a lack of data governance.

    Once problems are detected, for example, data silos, lack of centralization, or errors in data entries, you should elaborate a work plan oriented to successful data governance. This plan has to guarantee data availability and quality. As last, it is necessary to understand this is a continuous improvement process and requires the compromise of everyone working with data.

    Barrier 3. Tools or solutions hard to use

    It is important to choose tools that meet employees’ needs. Since the market has a wide range of solutions finding the right match is crucial. This match should take into account companies’ needs and data vision.
    In this sense, a mismatch happens when the tool is too inflexible and limits users’ operations in terms of access and interaction with data. On the other side, we can find self-service solutions with an excessive stock of options which might lead users to an overwhelming experience. In both cases, users tend to quit and go back to Excel.

    As an additional recommendation, providing users with the proper companion in topics like training and support makes a big difference, especially for those novel users in your team.

    Another difficulty, beyond tools selection, is the poor design of data models that do not fit users’ needs and limit what they can do with data. It is the same story when dashboards have the wrong parameters or are overloaded with them.

    Last point but not least, pay attention to the speed of queries. If this is too slow, the experience for users will be deprecated. Make sure your infrastructure setup can guarantee it.

    Barrier 4. Lack of data culture

    Organizational culture is important to foster changes in companies, and business intelligence adoption is not the exception. That is why it is necessary to work involving the whole team.

    Every employee needs to be aware of their role and fulfill it. C-level executives must lead change with their own example by using the BI tool themselves and encouraging their teams to use it. Otherwise, the way to a mature data culture will be impossible, and the acquisition of any business intelligence tool will be useless.

    Middle managers should prioritize projects that can provide early victories to help their teams to incorporate Business Intelligence tools. Working all together will achieve a business intelligence adoption across all the organization.
    As we mentioned before, identifying these barriers is crucial to overcoming them. In that sense, choosing a tool at the BI4Web level is an important step to having the necessary bases to overcome the barriers. With BI4Web, you can have the flexibility your users need without sacrificing data governance. They can access analytic documents according to permissions and navigate through them at the level of detail users might need.

    Another remarkable contribution of BI4Web to business intelligence adoption is to have a short learning curve, so you will not have to invest too many resources for your team training.

      Tips for dashboard designing

      Tips for dashboard designing

      by Business

      A dashboard well designed is a very important asset when making decisions, that is why we bring these tips that can help you to succeed in your next dashboard design.

      With this advice, you will get readers to focus on what actually matters not on distracting elements.

      Before beginning, we share with you a list of concepts we will be using in this article.

      • Dashboard: It is a set of representations that help to monitor and analyze in a visual way one or several concepts.
      • User: Is who will be using the information to answer questions with dashboard help.
      • Graphic representation: It is the representation of data using visual resources, some examples are: bar graphics, a gauge of state, treemap, etc.
      • Hierarchical representation: It is a subset of graphic representations, which organizes data in a tree structure or uses father/son relations.
      • Context: Physical environment or situation in which the meaning of what is talked about depends

      With these concepts clarified, we share with you our list of useful tips to improve your dashboards.

      Use the same colors to represent the same things

      To make it easier for the user to visualize and understand the context, it is recommended that you assign and use a specific color for each concept. In this way, the user will not have to see the legend of all graphic representations, at all times, but at a glance, they will know what concept you are talking about.

      When assigning colors to concepts, be aware some colors have a strong connotation and this might distort the reader’s perception. That is the case for red, yellow, and green which usually represent a rate of bad, regular, and good.

      For example, if you are doing a sales graphic and use the color red in the representation, the first impression would be negative, even if that is not the case.

      Do not forget to keep clean lines

      Give the information the space it needs, do not place it all in the same spot, nor use 3D effects, something very 90s and with a great power to distract. As we mentioned at the beginning of this article, a dashboard has to be easy to consult and does not need any effort to differentiate elements.

      This is an example of what a chart looks like with no space being given. In this case, it is impossible to visualize the data that is between 60% and 100% of the X axis. The overlapping of elements makes this chart useless to visualize all the data.

      What solutions can be proposed? One option would be to change the scale of horizontal from linear to exponential, another option would be to filter by continent or finally evaluate how relevant the area of the circles is and replace it with a scatter chart.

      Do not use 3D graphic representations

      There are not as many cases where 3D representations are effective. One of their biggest problems is they tend to hide information because of overlapping, keep in mind we are representing information in a 2D support (paper or screen)

      In this graphic, we can see when information is hidden. The overlapping here is that bad, that it is impossible to answer the question, how many people watch TV more than 4 hours a day?

      To answer that question we need to see the information represented in the green color of the text, how many hours do you watch per day? (¿Cuántas horas al día ve?) But, since all the other concepts hide it completely it is impossible to see.

      A solution that might come to your mind is to add a control to rotate the graphic, but it is important to remember the previous point and keep user attention focused on information and not on unnecessary and distracting efforts.

      Take into account graphics bar should start at 0 in the value exis

      Remember, our comprehension is very visual, mostly because more than 50% of our brain is intended to process visual information. Making it easier for us to remember physical features like the difference in the size of two objects that the actual value they represent. This is why if graphic bars do not start at 0 it becomes more difficult for readers to have an accurate perception and misunderstand the information.

      In this example, you can see how the X axis starts at 200 and creates an illusion that looks like on 12th September there were double of visits and clicks as on 27th October.

        IOT Solutions World Congress

        Visit us at the IoT Solutions World Congress

        by Business

        We are glad to invite our community to join us at the IoT Solutions World Congress. In this important event you will be up to date about trends and advances related to Internet of Things. You can meet us at Barcelona Deputee Booth in Fira between May 10th and May 12th. .

        The attendees will have the chance to vist the most known exhibitors, listen to top speakers and participate in different activities like testbeds, which are experimentations platforms with real life emulated conditions to prove solutions based in new services and technologies.

        What will you see in our stand?

        You will have first hand information of our products.

        Data Gate: A data hub with artificial intelligence, ideal to extract information straight from machines, PLC´s, among many other data sources. Read more here

        BI4Web: Our business intelligence tool takes data visualization to the next level with real time connection and a wide representations catalog. Read more here

          Entrada blog vocabulario visual

          How to choose the right graphic?

          by Business

          Choosing the right graphic is a key step to represent information properly. This is why we are giving you a list of recommendations that will help you to pick up the graphic that meets better your needs.

          You can start asking questions like: What type of values are you going to represent? What relation is there among values? How many series do I need to define? This way you can narrow your options. After solving these questions, choose the category that suits your representation needs better:

          Deviation: Emphasise on variations in relation to a reference point, usually this point is zero, but it also can be a target value or a long-term average value.

          Examples: commercial superavit/deficit or climate change.

          Correlation: Shows relations between one or more variables. Keep in mind if you do not indicate otherwise, most readers will understand shown relations as causals, it means one is caused by the other.

          Examples: inflation and unemployment, incomes, and life expectancy.

          Ranking: It is recommended when an item’s position in an ordered list is more important than its relative or absolute values. Do not doubt to highlight interesting points.

          Examples: wealth, privation, league positions, democratic election result.

          Distribution: This shows values in data sets and how frequently they happen. How distribution is made might be helpful to highlight lake of uniformity or equality in data.

          Examples: income distribution, population distribution (age/sex), inequitiy.

          Magnitude: Shows size comparisons. These can be relatives (only being able to see the biggest differences) or absolutes (seeing small differences is a must)

          Usually shows amounts as dollars, people or barrels, but no percentages or calculated rates.

          Examples: raw materials production, market capitalization, and volumes in general.

          From a part to the whole: It shows an entity in its constitutive elements. If the reader’s interest is only focused on component size, consider using a magnitudes graphic instead.

          Examples: Fiscals budget, company structures, national elections result.

          Spatial: Besides location maps, they are used only when precise location and graphic patterns in data are more important to readers than anything else.

          Examples: Population density, natural resources location, risk or impact of natural disasters, captation zones, election results variations.

          If you want to read more about this topic, download Guide: Visual vocabulary of RCM Software, clicking here

            Barcelona connectivity-min

            RCM Software at Mobile World Congress in Barcelona 2022

            by Business

            We start this 2022 with excellent news, we will be participating at Mobile World Congress for the fourth time, three of them in Barcelona and one in Los Angeles.

            Visitors will have the chance to get to know RCM Software novelties first hand, in products such as BI4Web and DataGate. With a special emphasis on Data Gate, our tool represents huge support for companies that are looking for an ally in their fourth revolution path. DataGate extracts data from any data source, this includes PLCs and processes it with machine learning algorithms. This way, companies can keep high-quality information to make decisions based on data, improving availability, performance, and quality.

            We encourage our clients, partners, and companies interested to visit us at CS180 stand between February 28th and March 3rd. in Fira Barcelona.

              Empleado con tableta-min

              Improve your production standards with IoT

              by Business

              The fourth industrial revolution is changing many things, but there are things that never change, for example, the KPI definition and the efficiency quest. In this context, tools and solutions play a very important role when collecting data straight from machines and delivering important information.

              However, data collection is not enough. It is necessary to have a wide and clear panoramic for defining actions needed to achieve full improvement. A key step in this path is defining KPIs, for example, overall equipment efficiency or OEE, which is useful for measuring the time a machine is producing at its maximum capacity and with optimum quality.

              This metric take into account three key factors: availability, performance, and quality. Keeping a record of these factors has a positive direct impact on OEE since it helps to identify where losses are happening. For this reason, IoT tools and solutions become allies that represent a big advantage. Here are some of them:

              Availability: Moving from corrective maintenance to a preventive and smart one

              It is impossible to avoid unavailability periods in machines since they need to be fixed once in a while, but it is possible to reduce those periods with preventive maintenance based on information extracted from machines like working records and waste derivated.

              With solutions like those offered by DataGate, it is possible to collect data from machines and store and analyze it. This way, you can know in advance when it will be necessary to schedule maintenance and not to do a corrective one, which tends to take more time since it is necessary to find out what happened, request the necessary pieces, and then do the actual maintenance.

              This is possible thanks to diagnosis based on machine learning done with data extracted from machines such as temperature, engine vibration, and other parameters. This way any deviation of parameters might work symptoms of a failure in the near future.

              In the same way, IoT sensors can tell in real-time the actual amount of available materials, so the machines do not have to stop because of a lack of them.

              Performance: Achieve and keep optimum performance levels

              Besides regular maintenance, there are some other short stops in production that can be related to materials stuck or components dealignment. These stops use to be ignored because of their fast resolution and small impact in the immediate term. However, the accumulation of this kind of event might turn into performance reduction or hide a bigger problem.

              With IoT, it is possible to know accurately where the failure occurred, and what parameter is out of range and this way find a timely and proper solution. Additionally, keeping a record of all regenerated data enables a full view of incidents with details like how frequently occur and how much time was required to solve them. This information helps teams to make better decisions, based on data, improving performance by eliminating or mitigating chronic issues.

              On the other hand, IoT helps to keep speed production at adequate levels, because it is possible to know if any factors such as lack of lubrication, environmental temperature, or dust are slowing down machines’ performance. Offering a 100% accurate answer to the reduction of indicators such as OEE.

              Quality: From beginning to the end

              Quality is another element part of OEE, taking into account it depends on many factors it is very important to quantify them and see their impact on the final result. It is in this matter that DataGate delivers a remarkable value because allows measuring variables of the own machines and other externals like environmental temperature that may influence in product´s quality.

              An important moment to implement improvements is when machines are starting production since usually defective products are made within this first moment. These improvements can be designed from learnings generated from machines’ data analysis and collection.

              In conclusion, working with a solution such as DataGate makes possible radical improvement of OEE because of the first-hand access to real-time and historical data, delivering relevant knowledge of different work fields. This knowledge is the fundamental base to make informed and timely decisions that contribute to reaching an OEE as close as possible to 100%.

                Grupo-de-trabajo-1

                5 keys to a successful data governance

                by Business

                To begin, it is important to define what data governance is. One of the most extended definitions says it is a work plan structure where is specified what person in the organization has the authority to control data and they can be used. The mentioned structure includes people, processes, and technologies necessary for data management and protection within the data life cycle.


                The Data Governance Institute defines it as: “A system of decision rights and responsibilities for processes related to information, executed following agreed models, which describe who can take action, what information with, when, under what circumstances and using what methods”.


                It is a very important part of data management strategy since it defines roles in the organization and its framework of action. This way, data management will not be a matter of individual definitions, but a coordinated action where everyone has a clear view of actions intended to collect, manage, secure, and to store data.


                What to do for successful data governance and data strategy?


                There are some standard steps useful to achieve such a mission. They include role assignation and their hierarchy. In the next paragraphs, you will find advice to be successful in following the mentioned steps.

                1. Involve your employees
                  Promote participation of your employees in the creation, implementation, and following of data governance policy. This way you will nurture an environment of interest and trust among them. Otherwise, it is very plausible lack of interest and trust leads to bad practices or not following the rules.
                1. Be aware of continued improvement
                  Hand in hand with the previous point, data governance requires organizations and their employees are aware these processes are suitable for updates in order to be more efficient or meet new regulations requirements such as GDPR. (General Data Protection Regulation) In this matter, a team with an open mind is a highly valuable asset.
                2. Create a glossary
                  It is crucial everyone within the organization is on the same page. This means there is an agreement in meanings and concepts of every element which is part of the data ecosystem, for example, do sales include the ones that have not been billed yet? This way, it will not exist different versions of the same information and corporational alignment will be accurate.
                  in the same way, it is very important to socialize the glossary with all the teams that work with data in the organization.
                3. Define roles and rules
                  This helps to make faster decisions, but it needs mechanisms that grant successful resolution of conflicts. A practical example is defining what people will be in charge of what data and what is the organization’s criteria for data management.
                4. Choose tools and solutions aligned with your vision of data governance.
                  Data governance is rather a company program of continuous improvement than a particular technology. Keep this in mind before investing in software so your purchase decisions will be aligned with your data governance vision and strategy. It is important to mention that business intelligence solutions are not an exception so choosing options that look after data integrity and processes optimization, will bring a lot of benefits themselves.

                A good example of how business intelligence can be aligned with best practices of data governance are those options that include centralization of data definition, it means a system of roles and permissions enabled to eliminate or mitigate risks of having different versions of data, such as BI4Web.

                Taking into account this advice, you can check on your organization’s status and create a plan to solve those areas suitable for improvement in order to enjoy all benefits of successful data governance. This helps organizations to be ready to monetize their data.

                  BI4Web New version 21

                  Learn what´s new in BI4Web version 21

                  by Business

                  The next version of BI4Web will deliver a faster and more agile performance and everything you need for a more intuitive work, both in visualization with BI4Web Viewer and in development with BI4Web Studio.

                  In this sense, BI4Web Viewer will have new kinematic components and the option to zoom in on specific data areas, which will offer a more interactive experience and open a new world in the visualization of details that increase your chances of finding out opportunities within data. In the same way, it will include direct access to exportation and changes in components’ behavior.

                  With this new release, planned for the last quarter of 2021, we offer our customers features that will give them better visualization options so they can continue to discover opportunities in data. To learn more about the update, we invite you to watch the following videos.

                  BI4Web Viewer version 21

                  Graphics designer tutorial. BI4Web Studio version 21

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