Search
START TYPING AND PRESS ENTER TO SEARCH

Data Solutions Provider Philippines

Tableau, AI, AI-Driven Insights, Starter Program
  • No Comments

Tableau and Exist Starter Program: Empowering Enterprises’ Data Insights Unleashed
Tableau and Exist Starter Program: Empowering Enterprises’ Data Insights Unleashed 839 630 Exist Software Labs

The Future of Business in the Philippines: AI and Analytics at the Forefront

In today’s rapidly evolving Philippine business landscape, artificial intelligence (AI) and analytics are not just tools—they are game-changers. AI automates processes, sharpens decision-making, and predicts market trends, while analytics transforms data into actionable insights that drive innovation in industries like retail, banking, and energy. For enterprises in the Philippines, embracing these technologies means optimizing operations, enhancing customer experiences, and unlocking new growth opportunities, making them indispensable for sustainable success in a digital-first economy.

On November 13, Exist Software Labs Inc., in partnership with Tableau, hosted an exclusive event aimed at empowering businesses with AI-driven insights. The event highlighted Tableau’s cutting-edge capabilities, showcasing how it enables smarter, data-driven decision-making. Attendees also gained access to a special starter program, offering exclusive discounts on Exist and Tableau’s innovative solutions.

Keep reading to discover the key takeaways from the event, insights into how AI and analytics are transforming industries, and how your business can leverage these technologies for a competitive edge.

Leverage on Exist Discoverex and Tableau to help make intelligent business decisions

Contact Exist for a consultation today!

Overview of the Exist-Tableau Starter Program Event

The event kicked off with a warm welcome from Exist’s VP for Engineering, Mr. Jonas Lim, who introduced the company and shared insights into Exist’s vision and the purpose behind this special event. He set the tone for the day, highlighting the importance of data-driven decision-making in today’s fast-evolving business environment. Following his introduction, Ms. Claire Claravall and Mr. Justice Dignos took the stage to showcase Tableau, demonstrating its powerful dashboard features and illustrating how it can transform raw data into actionable insights for businesses.

Tableau, AI, AI-Driven Insights, Starter Program

Event Highlights:

  • Introduction to Exist and Tableau
    The collaboration between Exist Software Labs and Tableau represents a natural synergy, combining our expertise in software development and data analytics with Tableau’s cutting-edge visualization capabilities. Together, we provide comprehensive data solutions that unlock valuable insights and empower organizations to make data-driven decisions across various industries.


  • Exploring Tableau’s Tools
    The session featured in-depth demos of Tableau Pulse, Tableau Prep, and Tableau Desktop, showcasing their practical applications for data managers and analysts. Claire and Justice, Tableau Account Executives, presented real-world use cases for data visualization tools, highlighting how attendees can leverage the full power of their organization’s data. They provided a comprehensive understanding of Tableau’s offerings, emphasizing their impact on driving actionable insights and improving decision-making.


  • Hands-On Demo of Tableau Prep and Desktop
    Our very own Nico Lim, Data Engineer at Exist, took the spotlight to demonstrate Tableau Prep and Tableau Desktop. He guided attendees through the Tableau environment, showing how data preparation tools can simplify the process of combining, shaping, and cleaning data from various sources. Nico illustrated how these tools help enterprises create analysis-ready datasets, making the transition to data visualization seamless.


  • Interactive Session and Product Launch
    The event featured an engaging interactive icebreaker, where attendees explored various Tableau dashboards hands-on. This immersive experience allowed participants to dive into the platform and interact with its powerful features, offering them a deeper understanding of how Tableau can revolutionize their data analytics processes.

Get your Free* Tableau license with Exist!

From Complexity to Simplicity: How Tableau’s AI Features Enhance Data Analysis

Attendees overwhelmingly praised the AI capabilities of Tableau, particularly its ability to simplify complex data analysis through features like Tableau Pulse and Tableau Agent. Many highlighted the live demos as a key moment, showcasing how intuitive and efficient Tableau is for building dashboards, preparing data, and generating insights. One attendee noted, “I really loved the demo on how Tableau works. I never imagined it could be this easy.” Another emphasized its convenience, stating, “It is more efficient to use than platforms like Excel.”

The event’s presenters also received commendation for their clear explanations and approachable style. Participants appreciated how the team effectively demonstrated Tableau’s applications in real-world scenarios, making it easier to visualize how the platform can transform their reporting and analytics. One attendee remarked, “The presenters were very accommodating and explained everything thoroughly, especially how Tableau can help streamline our processes.”

Participants left the event with actionable takeaways they could apply in their work. Many were impressed by Tableau’s drag-and-drop dashboard-building feature, advanced data preparation tools, and AI-driven insights for forecasting and root cause analysis. A participant noted, “It will definitely improve our company reporting and make it easier for the C-level to digest data interactively.”

Other key insights included learning about the ETL (Extract, Transform, Load) framework, Tableau’s AI features like Einstein Discovery, and the importance of data visualization in making data-driven decisions. For some, the event provided new perspectives on how to streamline their current reporting processes, with one attendee sharing, “This will make report generation hassle-free by just using Tableau or asking Tableau Agent to generate credible reports.”

Tableau, AI, AI-Driven Insights, Starter Program

Create Your First Dashboard with Tableau

Read more

Learn about Exist and Tableau Partnership 

Exciting Opportunities Ahead: Tableau and Exist Continue to Drive Data-Driven Success

In conclusion, the event effectively showcased Tableau’s transformative capabilities, leaving attendees eager to leverage the platform’s potential within their own organizations. As a special offer, participants can access the Exist-Tableau Starter Program Package at a discounted price, available until December 31, 2024.

Looking ahead, Exist and Tableau are committed to empowering more organizations to embrace AI and analytics tools, driving smarter, data-driven decision-making. If you missed this event, stay tuned for future announcements and articles to ensure you don’t miss out on exciting opportunities, valuable insights, and more in upcoming sessions.

Tableau, AI, AI-Driven Insights, Starter Program

Discover more about what your Data can do to you. Talk to us

    Which services are you interested in?

    Software DevelopmentTechnology ConsultingQA and TestingBig Data and AnalyticsSystems IntegrationMobile App DevelopmentBlockchain App DevelopmentDevOps

    Data Visualization with Tableau Dashboard
    • No Comments

    Tableau Dashboard Tutorial by Exist: Step-by-Step Guide
    Tableau Dashboard Tutorial by Exist: Step-by-Step Guide 839 630 Exist Software Labs

    Making informed decisions through the help of data is significant for any organization’s success. Analytical dashboards by Tableau serve as powerful tools that transform raw data into meaningful insights, helping decision makers to monitor performance, identify trends, and unleash opportunities. By providing a visual representation of key metrics and data points, dashboards simplify complex data analysis and facilitate quick, informed decision-making.

    Enterprises rely on data-driven decisions for competitiveness and growth. Yet, raw data must first be transformed into actionable insights that are accessible to decision-makers across departments. Monitoring and optimizing operational performance across functions like sales, marketing and finance pose challenges without effective tools, hindering the identification of inefficiencies or improvement opportunities. Handling large volumes of diverse data manually or with basic tools proves inefficient and time-consuming, highlighting the need for robust data visualization tools like Tableau to streamline analysis and enhance decision-making processes.

    In this blog, we will guide you step-by-step through the process of building your first analytical dashboard using Tableau. Tableau is a leading data visualization tool known for its user-friendly interface and robust analytical capabilities. By the end of this guide, you’ll have a clear understanding of how to start leveraging your data to work for you. 

    Leverage on Business Intelligence tools to help make intelligent business decisions

    Contact Exist for a consultation today!

    Let’s begin, to better understand what you want to achieve in your first Tableau dashboard you have to…

    Step 1: Define Objectives and Identify Key Metrics 

    • Clarify your goals by outlining what you aim to achieve with the dashboard, such as monitoring key performance indicators (KPIs), tracking user behavior, and identifying trends. You should also consider identifying stakeholders by determining who will use the dashboard and what specific insights they need.
    • Choose Relevant Metrics: List metrics that align with your objectives. Examples include:
      • Sales Metrics: Revenue, profit margins, sales growth.
      • Marketing Metrics: Conversion rates, customer acquisition cost, return on investment (ROI).
      • Operational Metrics: Process efficiency, resource utilization, downtime.
    Data Visualization with Tableau Dashboard

    Step 2: Collect, Clean and Prepare Data

    Collect Data 

    • Data Sources: Identify and integrate various data sources (e.g., databases, CRM systems, marketing platforms).
    • Data Extraction: Use tools and techniques to extract relevant data (e.g., SQL queries, API integrations).

    Clean and Prepare Data

    • Data Cleaning: Handle missing values, remove duplicates, and correct errors.
    • Data Transformation: Aggregate, normalize, and format data to ensure consistency and usability.
    Get your Free* Tableau license with Exist!

    Step 3: Analyze Data 

    • Exploratory Data Analysis (EDA): Use statistical methods and visualizations to explore the data and identify patterns or anomalies.
    • Segmentation: Break down data into meaningful segments (e.g., customer demographics, geographic locations).
    Tableau, Visualization

    Understanding the importance of business intelligence tools

    Read more

    Step 4: Design the Dashboard

    • Plan the Layout: Design a user-friendly layout with intuitive navigation and clear organization of information.
    • Visualization Techniques: Choose appropriate visualization types (e.g., bar charts, line graphs, pie charts) to represent different data points.
    Data Visualization with Tableau Dashboard

    Learn about Exist and Tableau Partnership 

    Step 5: Build the Dashboard

    • Create Visualizations: Develop the visual elements based on your design plan.
    • Integrate Interactivity: Add interactive features like filters, drill-downs, and tooltips to enhance user experience.
    • Ensure Responsiveness: Optimize the dashboard for various devices and screen sizes.

    read more

    Data Management, AI, Java Developer, Java. Developer in the Philippines
    • No Comments

    How to Maximize AI potential through Data Maturity for Innovation and Growth this 2024
    How to Maximize AI potential through Data Maturity for Innovation and Growth this 2024 839 630 Exist Software Labs

    In today’s data-driven world, organizations are increasingly turning to artificial intelligence (AI) to unlock valuable insights and drive innovation. However, the success of AI initiatives heavily depends on the quality and maturity of the underlying data. In this blog post, we’ll explore how data maturity plays a crucial role in preparing your data for AI applications.

    Understanding Data Maturity

    Data maturity refers to the level of readiness of an organization’s data management processes. It encompasses various aspects such as data quality, accessibility, governance, and integration. A high level of data maturity indicates that an organization has well-defined processes in place to manage its data effectively. The value of data maturity for AI lies in its ability to enhance model accuracy, reliability, and performance, leading to better insights, decision-making, and ultimately, business outcomes. Essentially, the better the quality and maturity of the data, the more effective and impactful the AI applications can be.

    Your organizations data maturity

    Data is the lifeblood of of transformative technology and Exist can help you prepare your data at any stage of your data maturity to be AI Ready 

    The Importance of Data Maturity for AI

    1. Data Quality: High-quality data is a pre-requisite for AI. It ensures that your data is accurate, consistent, and reliable, which is essential for training AI models and making accurate predictions. The better quality of the data, the more effectively you can leverage your AI for improved decision-making and gain valuable insights.
    2. Data Accessibility: AI algorithms require access to a wide range of data sources. A mature data environment ensures that data is accessible across the organization, enabling AI applications to leverage diverse datasets for analysis.
    3. Data Governance: Data governance frameworks ensure that data is managed in a transparent, compliant, and ethical manner. This is critical for AI applications, as they often deal with sensitive data and require strict controls to protect privacy and ensure regulatory compliance.
    4. Data Integration: AI models perform best when they have access to comprehensive and integrated datasets. Data maturity enables organizations to break down data silos and integrate disparate data sources, providing a more holistic view of their data landscape.

    Start Your Data Maturity Assesment Here:

    Steps to Achieve Data Maturity for AI Readiness

    1. Assess Current Data Practices: Conduct a thorough assessment of your organization’s current data management practices, identifying areas for improvement and opportunities for optimization.
    2. Implement Data Quality Controls: Invest in tools and processes to monitor and improve data quality, including data cleansing, deduplication, and validation techniques.
    3. Establish Data Governance Policies: Develop robust data governance policies and procedures to ensure data integrity, security, and compliance with relevant regulations.
    4. Invest in Data Integration: Implement data integration solutions to consolidate and harmonize data from different sources, enabling seamless access and analysis for AI applications.
    Data Maturity, Data, Data Analytics, AI

    Brad Edwards explained in his article the importance of Data Maturity to build solid ground for AI. According to his article, a company’s data maturity level is assessed based on its proficiency in utilizing data for analytics, machine learning, and decision-making. Companies with a higher data maturity tend to possess advanced AI capabilities and services, which play a crucial role in the effectiveness and achievements of their machine learning endeavors. With their high data maturity, A company can deploy AI models to predict consumer behavior, optimize inventory management, and personalize marketing campaigns. For instance, their AI-driven recommendation system analyzes historical purchase data, online browsing behavior, and customer feedback to suggest products tailored to individual preferences, leading to increased sales and customer satisfaction. You can read more about it here.

    Data Management, AI, Java Developer, Java. Developer in the Philippines

    Before AI, Data Maturituy (Successful AI Projects are Built on Solid Ground)

    Conclusion

    In the age of AI, data maturity is a prerequisite for success. By investing in data quality, accessibility, governance, and integration, organizations can ensure that their data is AI-ready and capable of unlocking valuable insights to drive business growth and innovation. Start your journey towards AI readiness today by prioritizing data maturity within your organization.

    Discover more about what your Data can do to you. Talk to us

      Which services are you interested in?

      Software DevelopmentTechnology ConsultingQA and TestingBig Data and AnalyticsSystems IntegrationMobile App DevelopmentBlockchain App DevelopmentDevOps

      Get your Free Exsight AI and Analytics Datasheet

        Sun Life Event: Spark Innovation Series- Cloud and Data Federation, Cloud & Data Federation, Data Solutions Philippines, Exist Data Solutions
        • No Comments

        Exist Software Labs discusses Cloud and Data Federation at Sun Life Global Solutions’ Spark Innovation Series
        Exist Software Labs discusses Cloud and Data Federation at Sun Life Global Solutions’ Spark Innovation Series 650 486 Exist Software Labs

        Cloud adoption has become increasingly essential for businesses looking to enhance their operations, improve scalability, and drive innovation. It allows organizations to leverage the power of cloud computing services to store, process, and analyze large volumes of data with ease.

        On Aug 29, 2023, technology experts and IT professionals converged at the Sun Life Centre, in Bonifacio Global City, Philippines. Exist Software Labs graced Sun Life Global Solutions’ Spark Innovation Series, which discussed, for that session, Cloud & Data Federation. The Exist Team shared their insights and experiences as a technology company, focusing on the importance of Cloud and Data Federation in an organization’s Data Maturity Journey.

        Cloud Adoption 3.0

        In today’s digital age, the adoption of cloud technology has become increasingly important for businesses. Cloud Adoption 3.0, the next phase of cloud adoption, is an innovation where organizations are not only leveraging the power of the cloud, but also embracing data federation.

        Sun Life Event: Spark Innovation Series- Cloud & Data Federation, Data Solutions Philippines, Java Developer Philippines, Cloud and Data Federation

        Exist Director of Tech Services Dennis De Vera focused his presentation on the implications, benefits, and uses of Cloud Adoption; including increased flexibility, scalability, and cost-effectiveness. Cloud adoption allows companies to store and access data from anywhere in the world, enabling remote work and collaboration.

        With the growing amount of data being generated by organizations, managing and analyzing this data becomes a challenge. According to De Vera, “This is where data federation comes into play. Data federation involves integrating and combining data from multiple sources or clouds into a unified view.”

        Cloud and Data Federation Strategies

        By adopting cloud & data federation strategies, businesses can unlock even more value from their cloud investments. They can gain deeper insights from their data by analyzing it holistically rather than in silos. This enables better decision-making, improved customer experiences, and enhanced operational efficiency.

        Furthermore, cloud & data federation also provide organizations with greater control over their data governance and compliance requirements. With centralized control over access permissions and security measures across multiple clouds or sources of data, businesses can ensure regulatory compliance while maintaining high levels of security.

        Implement Cloud Adoption and Data Federation to leverage on your cloud investments now

        CONTACT US

        What part does security play?

        Whilst cloud & data federation integrate resources across multiple platforms and servers, it also introduces potential vulnerabilities that must be addressed to maintain a secure environment. Protecting secure assets, such as sensitive customer information or proprietary business data, requires strong access controls, encryption mechanisms, and authentication protocols. 

        Regular audits are crucial for maintaining security within a federated environment and identifying potential weaknesses or compliance gaps. By examining security controls across different platforms and servers, organizations can proactively address vulnerabilities before they are exploited by malicious actors.

        Security plays an integral part in the Cloud & Data Federation. By implementing robust encryption measures, conducting regular audits, and enforcing strict access controls, organizations can protect their valuable assets while leveraging the benefits of federated environments effectively.

        Know more about what cloud adoption and data federation can do, specific to your organization

        CONTACT US TODAY

        Don’t know where to start with cloud adoption? Exist is a multi-awarded technology innovator that provides free technical consultation to help you jumpstart your cloud adoption, cloud federation, and data maturity journey. Discuss with our experts to maximize the benefits of digital transformation today.

        Understanding the Importance of Business Intelligence Tools Business Intelligence Tools, Data Ready, Data-Driven Era, Java Philippines, Data Solutions Philippines
        • No Comments

        Understanding the Importance of Business Intelligence Tools
        Understanding the Importance of Business Intelligence Tools 650 486 Exist Software Labs

        In today’s data-driven world, being data-ready is crucial for organizations to gain insights, make informed decisions, and stay ahead of the competition. Business Intelligence tools (BI), such as Tableau and Power BI, play a pivotal role in empowering businesses to harness the full potential of their data. In this blog post, we will explore the importance of being data-ready and delve into the capabilities of these two popular BI tools.

         

        Business Intelligence Tools: Understanding the Importance of Being Data Ready

        Being data ready means having the necessary mindset, processes, and infrastructure to effectively collect, manage, analyze, and visualize data. It enables organizations to uncover valuable insights, identify trends, and make data-driven decisions. Being data-ready offers several advantages, including:

         

        • Improved Decision-Making: With comprehensive data analysis, organizations can make more informed decisions based on customer behavior and preferences, among others, leading to better product and service design and increased competitiveness.

         

        • Identifying Opportunities and Risks: Being data-ready allows businesses to identify emerging opportunities, potential risks, and market trends, enabling them to adapt and seize competitive advantages.

         

        • Enhanced Efficiency and Productivity: By streamlining data processes and providing easy access to insights, being data-ready boosts operational efficiency and empowers teams to work more productively.

         

        • Customer-Centric Approach: Leveraging data helps organizations understand customer needs, preferences, and behavior, leading to personalized experiences and improved customer satisfaction.

        Leverage on Business Intelligence tools to help make intelligent business decisions

        Contact Us

        Benefits of Using Business Intelligence Tools 

         

        • Data Consolidation and Integration

        One of the primary benefits of BI tools is their ability to consolidate and integrate data from multiple sources. Companies generate data from various platforms such as on-ground sales transactions, customer interactions, marketing campaigns, and supply chain operations. BI tools aggregate and organize these diverse data into a unified view, providing decision-makers with a comprehensive understanding of the business landscape.

         

        • Real-time and Historical Analysis

        BI tools offer real-time and historical analysis capabilities, giving businesses the ability to monitor their operations as they unfold and examine past performance trends. This dynamic feature empowers executives to make agile decisions in response to changing market conditions and identify long-term patterns that can shape future strategies.

         

        • Enhanced Data Visualization

        Raw data can be overwhelming, making it challenging for decision-makers to grasp crucial insights quickly. BI tools address this challenge by providing advanced data visualization techniques. Interactive dashboards, charts, graphs, and reports transform complex data into intuitive visual representations, making it easier to comprehend and identify key trends, patterns, and outliers.

         

        • Informed Decision-Making

        BI tools enable data-driven decision-making, which is critical in today’s fast-paced business environment. When armed with accurate and timely information, executives can confidently make informed choices that align with business goals, leading to more effective strategies and improved outcomes.

         

        • Improved Operational Efficiency:

        By streamlining data analysis and reducing manual reporting tasks, BI tools enhance operational efficiency. Employees can focus more on strategic initiatives rather than spending valuable time collecting and collating data. Moreover, with automated reporting features, BI tools facilitate the seamless distribution of insights across departments, fostering collaboration and alignment.

         

        The Data-Driven Era

        In today’s data-driven era, being data-ready is essential for organizations to thrive. Tableau and Power BI are powerful BI tools that empower businesses to unlock the true potential of their data. By leveraging intuitive data visualization, seamless data integration, advanced analytics, and collaboration features, these tools enable users to make data-driven decisions, enhance operational efficiency, and gain a competitive edge.

        Know more about our Data Solutions services here

        Contact Us Today

        Exist offers data solutions services and Business Intelligence tools you can use to make informed decisions, and stay ahead of the competition. Start with your journey to data maturity and become a data-driven organization!

        About the Author

        Mark Daryll De Venecia is a highly motivated and skilled data engineer with a passion for harnessing the power of data to drive meaningful insights and innovation. He has successfully obtained several certifications that attest to his proficiency in data management, data integration, and data warehousing. These certifications, combined with his problem-solving abilities and meticulous attention to detail, enable him to design and implement robust data solutions that empower businesses to make data-driven decisions efficiently and effectively. Mark continually seeks to expand his knowledge and stay at the forefront of emerging technologies in the dynamic field of data engineering.

        DevOps. Java. Java Developer. Data Solutions. Data Solutions Provider Philippines
        • No Comments

        Nine (9) Effective Ways DevOps Minimizes Technical Debt
        Nine (9) Effective Ways DevOps Minimizes Technical Debt 650 486 Exist Software Labs

        DevOps is an amalgamation of philosophies, practices, and tools that addresses numerous developmental and operational challenges an organization faces, one of which is dealing with ‘technical debt’.

        Technical Debt is accrued when less-than-ideal coding and design decisions are made – in order to get what the team requires now or if there is a need to go into production sooner.

        TEST IN THE EARLY STAGES OF SOFTWARE DEVELOPMENT

        This is a key DevOps Practice, to test early in the Software Development Lifecycle (SDLC), testing early is also known as “Shift-Left Testing”. It assists in finding and preventing errors from the early stages of the delivery process. It includes code coverage analysis, static code analysis, unit tests, as well as other code-level practices to catch errors at the earliest time possible where they cost the least to fix.

        IDENTIFY AND RESOLVE MAJOR PROBLEMS FIRST

        The DevOps Lifecycle has lean, short feedback cycles and faster iterations due to the enhanced level of collaboration between teams. This results in not having to wait until the next feature release to get a fix for bugs, security vulnerabilities, and usability issues, in addition, major complications that can affect users or operations are fixed instantaneously.

        The process can be optimized further by defining a ranking for problems from low to high priority to help in deciding which issues should be attended to first. The team should be focus on solving these major problems first and not leave anything for a later time down the line.

        CREATE IMPROVED COLLABORATION BETWEEN THE DEVELOPMENT AND OPERATION TEAMS

        A possible reason for incurring technical debt or “code debt” is because development teams, regardless of how reluctant they are, may be forced into taking shortcuts to deliver on tight deadlines combined with struggling with constant changes or requirements. However, improving the collaboration between the Development and Operations teams can shorten the SDLC, and enable quicker deployments, in addition to increasing their overall frequency.

        Continuous Integration/Continuous Deployment and Continuous Testing can make it easier for teams to navigate and deal with changes. In general, cultivating a collaborative culture inspires code reviews, good coding practices, and robust testing with mutual help.

        HIGHLIGHT MORE AUTOMATION

        In automating tedious time-consuming tasks, and others that prove to be more prone to errors, your teams will be granted more time to repay technical debt. Additionally, automation that is rooted in CI/CD, in terms of automated testing and building, and Infrastructure as Code (IaC) supports in recognizing debt earlier and facilitates continuous debt repayment. It also enforces code quality standards – hence, automation can reduce existing technical debt while also preventing any future debt.

        MANAGE TECHNICAL DEBT

        DevOps makes it easier to control and manage technical debt continuously. It empowers constant communication, allowing teams to track debt, incite awareness and resolve it as soon as possible. The appointed team leaders can also include a review of the technical debt into backlog and schedule maintenance sprints to deal with it promptly. DevOps also reduces the likeliness of having incomplete or deferred tasks in the backlog, further helping prevent incurring any additional debt.

        CULTIVATE A DEVOPS CULTURE

        In managing technical debt over long periods, a proper DevOps Culture will be the key. As we’ve said a number of times over, it encourages strong collaboration between cross-functional teams, provides autonomy and ownership, and practices continuous feedback and improvement. It’s a truly efficient platform in calculating and tracking technical debt whilst communicating it to other teams. A DevOps Culture can also be used as a way to educate and inform developers of the kind of codes that may introduce bugs and raise code quality.

        DEFINE YOUR DEVOPS STANDARDS

        A well-defined DevOps Standards will allow you to create quality gates for every code check-in before running tests and deployment. It saves your teams from repetitive, prone-to-error tasks while optimizing their development efforts. In enforcing certain DevOps Standards, it can also prevent your teams from cutting corners in the process, which is the major contributor to technical debt, thus, implementing exact DevOps Standards can maintain a high level of productivity and quality while ensuring excellent team morale and indirectly saving money for your organization.

        SMOOTHER DEPLOYMENT PROCESS

        You should consider utilizing containers to make deployments easier, containers are lightweight and portable and can simplify application development and deployment. A container orchestration tool like Kubernetes, automates container lifecycle in production, allowing your teams to focus on high-value tasks of refactoring apps. or lowering code debt.

        APPLICATION PROGRAMMING INTERFACE (API) FIRST MODEL

        The way application components communicate with one another is also critical in addressing technical debt, which can also be caused by different systems accessing services and data in ways that are unexpected to the team. If you implement APIs, it can make the interfaces more visible and increases the resilience of communications, due to bad links between different applications, an API-based model permits teams to make changes quickly without affecting the existing structure. In addition, any team that interacts with the service in question at a later date has a clearly defined set of expectations, as a result of this, it’ll be easier to roll out any changes/features with less technical debt.

        Are you ready to make the most of your data to set your company up for success? Let Exist Software Labs, Inc. help you start your Data Maturity Journey today!

        Enter your
        text here