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The Philippines’ Most Respected

Griffith Data Innovations is the Philippines’ premier data analytics agency. Forged by decades of experience in working businesses of all sizes from a wide range of industries, we have use powerful technologies and unparalleled expertise to help clients run smarter enterprises.

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In a world where going digital is the norm, data is essential in better understanding the realities of your business. When it comes to data analytics, Griffith goes far beyond simple reports. We help enterprises extract, secure and process big data using cutting-edge technology driven by proven data science principles. Our goal is to provide an irrefutable information beacon that guides your most crucial business moves while maximizing operational efficiency.

Data analytics Unlocks the Power of your Business

Here’s why our clients have chosen to embrace data analytics with Griffith’s help.

Enhanced Decision Making

Move beyond estimation and intuition. Make your decisions with confidence backed by evidence-based insights provided by data analytics.

Process Automation

With machine learning techniques, business processes such as estimation, forecasting, classification and decision-making can be streamlined and automated, saving you precious time and resources associated with manual analysis.

Increase Revenue

Grow your bottom line with data analytics. Discover new opportunities, optimize your pricing strategies, and enhance your marketing effectiveness for meaningful gains.

Boost Operational Efficiency

Stop bleeding time, money, and man hours. Identify bottlenecks, waste, and underutilized resources in your organization to maximize performance.

Understand Customers Better

Data paints a much clearer picture of your target customer better than words and anecdotes. Use this insight to better target people’s pleasure and pain points.

Reduce Risks

Don't leave anything to chance. Uncover hidden data patterns and correlations that signal potential issues that you can address even before they get started.

Forecast Your Future

Today’s data is the barometer for tomorrow’s events. Use analytics to see where the market is heading to mitigate risks and capitalize on opportunities.

Brands We’ve Helped

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Our Services

Data Mining

Griffith’s expert team uses powerful technologies to extract massive amounts of data, then sifts through it to separate valuable information from the noise. We make sure that your data is clean and accurate for it to serve as a reliable basis for future analyses.

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Business Intelligence

We convert raw data into actionable insights, enabling informed decision-making and forecasting for your enterprise. Our business intelligence services empower you to visualize data in an easily understandable format, fostering quicker and smarter business decisions.

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Advanced Data Analytics

We don't just compile and report data: we extract real-world value from it. Attribution modeling, customer segmentation, and user behavior analysis are just some of the things we do for our clientele.

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Machine Learning Modeling

Our team at Griffith builds sophisticated machine learning models that learn from your data and adapt over time. These models are designed to predict outcomes, automate decision-making, and streamline your operations to maximize workflow efficiency.

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Big Data Processing

We understand that managing and making sense of massive volumes of data can be overwhelming. That's why our experts are here to handle your big data processing needs, using advanced analytics to help you derive real-time insights and solutions from the ocean of your data.

Data Warehousing

Our data warehousing services provide a robust, secure environment for consolidating your data across the organization. This means you can store, access, and analyze your data from a single, unified platform.

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Industries We Help

Healthcare

Data analytics optimizes patient care, predicts disease patterns, and improves operations, driving significant health outcomes.

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Retail

We help retail businesses measure results, understand consumer behavior, optimize pricing, and predict market trends for increased profitability.

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Finance and Banking

Our analytics detect fraud, streamline processes, and personalize customer service in financial institutions, maximizing revenue and mitigating risks.

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Marketing

We use data analytics to optimize marketing campaigns and accurately measure ROI, so you can invest in what works and save on what doesn’t.

Supply Chain and Logistics

We help you extract and process reliable data to improve supply chain efficiency, manage inventory, and boost your bottom line.

Telecommunications

Our analytics improve service reliability, forecast network usage, and enhance customer experience in the telecommunication sector.

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Manufacturing

We help manufacturers improve product quality, streamline operations, and predict equipment failures with data analytics.

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Travel and Tourism

Data analytics leads to personalized customer experiences, optimized pricing, and effective marketing in the travel and tourism industry.

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Education

We help academic institutions improve student outcomes, optimize resources, and predict future trends, supporting strategic planning in educational institutions.

Real Estate

We help real estate businesses understand market trends, evaluate property values, and predict investment outcomes through data analytics.

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Government

We use data and technology to help government agencies improve public services and make better policy decisions.

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Pharmaceuticals

We leverage data in a wide range of applications from patient safety improvement, marketing, inventory and more.

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Hospitality

We use data analytics to enhance guest experiences, optimize pricing, and improve operations, driving customer loyalty and profitability in the hospitality sector.

Our Process

Together, we dive into your business, understand your unique goals, and pinpoint how data science can provide solutions. Whether it's predicting sales, segmenting customers, or enhancing supply chain efficiency, we're here to address your needs.
Problem Definition
Problem Definition
We assemble the crucial data from various sources such as transactions, customer databases, and online behavior. With us, the complexity of this initial step is no longer your concern.
Data Gathering
Data Gathering
We tackle the messy data, manage missing values, outliers, and inconsistencies, effectively transforming your raw data into reliable information ready for analysis.
Data Cleaning and Preprocessing
Data Cleaning and Preprocessing
We unlock the hidden patterns and correlations in your data. By visualizing and interpreting the narrative your data presents, we set the stage for advanced modeling.
Exploratory Data Analysis
Exploratory Data Analysis
Based on our insightful analysis, we create potent new features and eliminate the irrelevant ones, ensuring your models have the best input for precise predictions.
Feature Engineering
Feature Engineering
Here's the exciting part: we develop a custom model, employing the most appropriate techniques - be it regression, classification, or clustering - dedicated to solving your unique problems.
Model Building
Model Building
Your model undergoes rigorous testing with a separate validation set and is evaluated using the most relevant metrics. This way, you can be fully confident in its performance before deployment.
Model Validation and Evaluation
Model Validation and Evaluation
Now, your model is ready for action. Deployed in a production environment, it empowers you to make data-driven decisions and predictions based on the latest data.
Model Deployment
Model Deployment
Our commitment doesn't end with deployment. We monitor your model's performance continuously and adjust it as necessary, ensuring its reliability as your business and data evolve. We're with you every step of the way.
Monitoring and Maintenance
Monitoring and Maintenance

What is Data Science?

Data science is an interdisciplinary field that leverages mathematics, statistics, and computer science to derive meaningful insights from large, complex datasets. Employing advanced algorithms, statistical models, and machine learning techniques, data scientists are able to decipher patterns, correlations, market trends, and customer preferences from this data, creating a robust basis for strategic decision-making and competitive advantage.

For key business decision makers, the role of data science in driving business growth and innovation cannot be overstated. Whether the objective is to enhance customer satisfaction, optimize operations, or anticipate market trends, data science delivers the requisite insights. By transforming raw data into actionable information, data science enables evidence-based decision-making, diminishing the need for speculation or intuition.

This leads to more precise forecasting, improved offerings, heightened operational efficiency, and subsequently, superior business performance. It is therefore crucial to perceive data science not merely as a technical tool, but as a strategic ally that equips your organization with the capability to confidently navigate the complexities of the contemporary business environment.

What is Business Analytics?

Business analytics is a comprehensive practice that utilizes data, statistical analysis, quantitative methods, and computer-based models to aid decision-making within organizations. It involves dissecting data through various analytical processes to identify patterns, correlations, and trends. This information is then used to predict future outcomes, optimize current operations, and solve complex business problems. Business analytics bridges the gap between data and actionable insights, enabling organizations to make decisions based on evidence rather than conjecture.

From a strategic viewpoint, business analytics is fundamental to driving innovation, enhancing operational efficiency, and gaining a competitive advantage. It enables business leaders to interpret vast amounts of data, and translate it into a roadmap for achieving commercial objectives. Whether you’re an executive who seeks to better understand your target demographics, or you’re planning ahead to make your enterprise more resilient to future disruptions, business analytics will help you make more informed decisions based on reliable data.

Data Science and Business Analytics FAQs

Data Science is an umbrella term that encompasses all aspects of data processing, including Data Analytics. Data Analytics is more focused on examining datasets to draw conclusions about the information they contain, usually through automated systems and software, whereas Data Science uses advanced techniques and algorithms to understand and predict trends.

Data Science can help businesses in various ways, such as improving decision-making by providing predictive insights, enhancing customer targeting through segmentation, optimizing business processes, and discovering opportunities for new products and services.

Key skills include knowledge of programming languages (like Python or R), statistics, machine learning, data visualization, and problem-solving. Domain knowledge and communication skills are also important.

A Data Analyst interprets data and turns it into information that can offer ways to improve a business. Their work involves creating dashboards, running statistical tests, interpreting results, and presenting findings to the team.

While both involve analyzing data, Business Analytics is typically more focused on using data and statistical methods to understand and improve business performance, while Data Analytics can be used in various fields and is not restricted to business scenarios.

Data Scientists use a variety of tools, including programming languages like Python or R, databases like SQL, big data frameworks like Hadoop, data visualization tools like Tableau, and machine learning platforms like TensorFlow.

A Business Analyst uses data to assess the processes, determine the business needs, and deliver data-driven recommendations to company executives to drive improvement and policy changes.

Yes, any industry with data can leverage Data Science. It’s widely used in sectors like healthcare, finance, retail, transportation, and more, for predictive modeling, data analysis, and optimization.

A predictive model uses statistics and machine learning to predict future outcomes based on historical and current data. It’s used in various domains, like forecasting sales, predicting customer churn, or estimating disease spread.

Big Data refers to extremely large data sets that are often too complex for traditional data-processing software. It’s characterized by 3 Vs: Volume (large amounts of data), Velocity (speed of data in and out), and Variety (range of data types and sources).

Big Data provides the rich, varied datasets that fuel Data Science. With more data to learn from, Data Science algorithms can create more accurate models and provide deeper insights.

The goal of Business Analytics is to enable data-driven decision making. It involves analyzing historical data to understand trends, measure performance, and use this information to drive business strategy and planning.

Ready to get started?

Reveal the untapped potential of your data. Start your journey towards data-driven decision making with Griffith Data Innovations today.

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