Data Solutions

Tableau, AI, AI-Driven Insights, Starter Program

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

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.

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

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

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    Data Visualization with Tableau Dashboard

    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

    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.

    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

    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

    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.

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

    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

    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.

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