Data science solutions
Bring your data to life and increase the value of your business with Miquido’s data science solutions
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Data Science consulting and development services
Never miss out on new business opportunities. Get actionable, data-driven business insights with our Data Science consulting company. We put our heads together to analyse and find patterns in your data, so we can advise you on your business strategy and answer your needs with a tailored solution that leaves competitors far behind.
Our Data Science services
Business Intelligence (BI)
BI is beneficial to business process management and validation. Your custom Business Intelligence dashboard can help you to understand your data better by showing only what is relevant to your set objective, and thus eliminating the “too much information” issue. That way, you’re able to stay focused, with a clear goal ahead, and save valuable time as a result.
Big Data
Making sense of complex data can prove to be a challenge, and that’s when Big Data comes to the rescue. It encompasses large datasets that cannot be handled by traditional computing techniques and processing software. Using Big Data solutions allows you to analyse information faster, reduce costs and introduce innovations. This way, you can make sure that your customers are delivered a polished product.
Extract, Transform, Load (ETL)
ETL is a process of extracting data from different sources, transforming it into a desirable format and loading into a destination location suitable for further business analysis (that can be Data Science, Business Intelligence or Machine Learning). Applying a customised ETL pipeline for complex data management and standardisation automates and simplifies the process, as well as improves its efficiency.
Data Mining
Data mining is useful when it comes to huge amounts of data that need to be made sense of. It helps you to turn raw data into useful and actionable information. In other words, data mining empowers your business with predictive analytics tools for discovering patterns hidden in large datasets, by involving methods at the intersection of machine learning, statistics and database systems.
Exploratory Data Analysis (EDA)
EDA is a statistical approach to analysing data sets and summarising their main characteristics. We can help to identify outliers and errors, the most common and missing values, visualise multivariable distributions, spot hidden natural or unusual patterns, and investigate relationships between variables and their strength. All these are crucial to discovering data and providing the necessary context to reach your business goals.
Text Mining
Text Mining is the process of deriving quantitative information from unstructured text. We can offer it as a separate solution or as a pre-processing phase of further text analysis using artificial intelligence and machine learning techniques, including natural language processing (NLP). You’ll be able to get in-depth insights into how customers interact with your brand, and automate manual processes like text document processing.
Tangible results, right on schedule
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Why should you use Data Science in your company?
Explore the most important benefits of implementing Data Science solutions to your business
Actionable business insights
When it comes to digital business, staying up to date is the key to success. Identifying business trends and pointing your organisation in the right direction helps to capitalise on new opportunities. See your company in a new light thanks to solid data and ensure its steady growth.
Data-Driven decision-making
Make certain your business goals are achieved while saving valuable time and resources. By measuring and tracking chosen KPIs and metrics, you can successfully reduce your costs and increase revenue at the same time, all thanks to the implementation of Data Science solutions.
Reduced data overload
Collecting data is crucial to ensuring business growth, but sometimes it can result in information overload that is difficult to understand and operationalise. Making data more understandable and useful by providing multiple data visualisation possibilities for users who aren’t skilled analysts is what data science is all about.
Audience-dedicated dashboards
Manage information properly, improve your operations and boost performance with personalised dashboards tailored to the audience using them. Depending on the user, strategic, analytical, operational, and tactical dashboards can be suited and designed for the desired application.
Product improvements
Knowing your user base’s needs is crucial for your product to become a hit on the market. Getting a 360° customer view helps to predict customer behaviour, identify user trends, deliver the right service at the right time, therefore helping to reduce customer churn rates and improving the chances of sales.
Ready to boost your business with Data Science?
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Where does Data Science excel?
development
delivered
conducted remotely
Apps we’ve built with Data Science services
Jazzed
Data analytics solution for music streaming app
Revolt
Advanced analytics tool for better understanding app user behaviour
Miquido was engaged throughout the project and responded well to the expeditious timeline. They were proactive in project management and understood the requirements and challenges.
Miquido’s team was well-organized and delivered on all their promises. Thanks to their expertise, the final products offer more features and integrations than originally expected.
They’re really smart people. It’s not just work for them; they are connected to the company.
Our tech stack
Data Processing
Python
Apache Spark
AWS Glue
Amazon EMR
Amazon Kinesis
Data storage
BigQuery
Delta Lake
PostgreSQL
Machine Learning
Amazon SageMaker
TensorFlow
Keras
Pandas
Business Intelligence
Google Data Studio
Power BI
Custom Data Science solution development
Want to find out more about Data Science?
Are you interested in Data Science solutions? Browse the most frequently asked questions and see what there is to learn!
What is Data Science used for?
Data science is a powerful tool that uses deep learning, machine learning, and math to analyse large and complex data sets. It allows us to extract insights and knowledge that can help us make informed decisions, improve processes, and drive innovation.
You may use data science to analyse customer behaviour, market trends, and other key metrics to make informed decisions and improve operations.
Data Science can help you to solve complex real-life and business-specific problems with the use of data. When the amount of available data is vast and traditional data analytics tools are no longer relevant, or when the business problems are complex, it’s time to turn to data science solutions.
What is the difference between Data Science and Data Engineering?
Data Science and Data Engineering are two related but distinct fields within the larger world of data analysis.
Data Engineering is all about building and maintaining the infrastructure that enables data to be collected, stored, and processed. It involves designing databases, pipelines, and other systems to handle large and complex data sets. Data Engineers ensure that data is organised, reliable, and accessible for analysis.
On the other hand, Data Science focuses on extracting insights and knowledge. It involves applying statistical methods, machine learning algorithms, and other techniques to identify patterns, make predictions, and inform decision-making. Data Scientists work on analysing data and extracting insights that can be used to solve problems and drive innovation.
To put it simply, Data Engineering is about creating the framework to enable data analysis, while Data Science is about using that framework to gain insights and knowledge.
How can Data Science help my business?
You can benefit from data science in various ways, no matter the industry:
Computer vision: Data Science allows for creating advanced video and photo recognition systems which can modify, improve or analyze videos and photos for every possible use case.
Fraud detection: Data science techniques such as anomaly detection and predictive modelling can be used to detect fraud in financial transactions, insurance claims, and other areas.
Recommendation systems: Online retailers, streaming services, and social media platforms use data science to build recommendation systems that suggest products, movies, or friends based on a user’s behaviour and preferences.
Personalised medicine: Data Science is used to analyse genomic data and identify genetic variations that can inform personalised disease treatments.
Traffic optimisation: Transportation companies use data science to optimise traffic flow, reduce congestion, and improve public transportation systems.
Climate modelling: Data science is used to analyse climate data and build models to predict future environmental changes and inform policy decisions.
Predictive maintenance: Manufacturing companies use data science to analyse equipment data and predict when machines might break down, allowing for preventive care and reduction of downtime.
Which industries use Data Science?
Retail and e-commerce companies use Data Science to understand customer behaviour and preferences, personalise marketing campaigns, and optimise pricing strategies. Social media platforms use it to recommend content, target advertising, and detect fake news.
Data Science is also used extensively in the healthcare industry. Medical researchers use Data Science to analyse patient data and medical records to identify patterns and trends that can inform new treatments and therapies. Hospitals and healthcare providers can use it to improve patient outcomes, reduce costs, and enhance the overall quality of care.
In finance, Data Science is helping companies manage risk, detect fraud, and develop investment strategies. Machine learning algorithms can analyse large financial datasets and predict market trends, enabling financial institutions to make better-informed investment decisions.
In transportation, Data Science optimises traffic flow, predicts maintenance needs, and improves safety. By analysing data from sensors and cameras installed on vehicles and roadways, data scientists can identify patterns in traffic and develop predictive models that help transportation providers make data-driven decisions.
Which industries can use Data Science?
Data Science applications in healthcare are well-established and highly impactful. They help in diagnostics, decision making and process automation. Through the consolidation of data from different sources (like medical records, drug intake and wearable data) we can get a big-picture view of patient conditions and identify unseen trends and relations. Faster diagnostics can also be supported by automatic segmentation and analysis of medical images.
See our solutions for healthcareIdentifying customers and understanding their needs is extremely important for e-commerce businesses. Data science solutions have a direct impact on both user experience and revenue. Analysing the path to product purchase and mapping a series of events leading to a defined goal will point out critical and vulnerable phases in the whole process. Furthermore, tracking app user activity and app functionality preferences makes for a continuous functionality improvement.
See our solutions for e-commerceWith our experience in the entertainment sector, we can help you adapt features and content to your target audience. To better understand your end users, we offer custom analytics and dashboards focusing on your KPIs. Additionally, customer sentiment analysis helps to classify posts and messages, and understand emotions hidden behind user opinions.
See our solutions for entertainmentWe will help you with data-driven financial planning for better management. Applying client segmentation results in targeted, fit-for-purpose marketing. Customer lifetime value analysis enables prediction of the profit made on each customer in future relationships. For a bigger picture, we may also offer business-specific risk analytics and fraud detection.
See our solutions for fintech
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