This page is dedicated to those who think of Big Data consulting and are still unsure whether or not they have Big Data. But don’t worry – we will help you figure it out!
Although Big Data is used in various industries, very few organizations really have it. We can often hear from companies with a few million rows of data that they have Big Data. But this is not usually the case. As a leading Big Data consulting company, there is a simple checklist you can follow to determine whether you really have Big Data or not.
Checklist to determine if you have Big Data in your company:
- You have over 1TB of data;
- You need real-time operations;
- Your data comes in multiple formats;
- Your current infrastructure (Microsoft Excel, relational databases, ETL systems) cannot handle your data anymore.
If at least one of the following is true for your company, you probably have Big Data and require decent Big Data consulting services. However, if your only problem is that your SQL script takes an hour to execute, you most likely don’t have Big Data.
Founder and CEO, Elafris Inc
CEO and Founder, Reply
Michael Korkin, Ph.D.
CTO at Entropix, Inc.
AI R&D center for US product company
Together with American colleagues, our team creates a solution based on Computer Vision / Machine Learning.
– Reduce injury risks and prevent accidents in steel production with AI.
– Assemble a team of 10 talented engineers in a month amid quarantine.
Beauty and health stores chain (Ukraine)
The largest national retail chain of beauty and health stores, offering more than 30,000 assortment items.
– Up-sell and cross-sell enabling through a recommendation system.
– Clients churn prediction
Solar panels installer (Netherlands)
Rooftop solar panels installation for residential houses.
– Label roof coordinates and types based on satellite images (R&D project).
Odin money (US)
Odin is a global mobile banking app that offers keeping all your bank accounts in one place. Bills and financial milestones track through one integrated experience.
– Create and use ML model for the classification of all transactions.
Marketing teams tend to have lots of data about advertising, web analytics, customer behavior, etc. We can fine-tune all data analysis solutions to run like clockwork and free up more of your marketing team’s time to be strategic and effective. Our data science services company uses machine learning to:
– forecast sales;
– recommend products;
– analyze assortment and so on.
2. Retail (E-commerce)
Retail usually accumulates large amounts of data and is eager to use data analytics.
We can help with:
– customer analysis;
– assortment analysis;
– sales forecasts;
– marketing and advertising budgets optimization;
– increase the efficiency of merchandising and supply chain management.
Generation of optimized plans that enable predictive maintenance is one of the key goals for AI in manufacturing, as well it helps in:
– optimizing production lines and logistic chains;
– forecasting revenue;
– determining optimal employee workloads;
– setting up automated systems for monitoring compliance with safety regulations.
When artificial intelligence is working with IoT devices it means that data can be analyzed and decisions can be made without involvement by people. In a broad variety of industries where IoT is implemented, AI can help to identify patterns and detect anomalies in the data that smart devices and sensors transfer (for example, air quality, humidity, temperature, pressure, vibration, sound, and others).
FinTech companies usually work with sensitive information and have high-security standards. We take all necessary precautions to keep their data safe. Data Science UA can assist such businesses in:
– credit scoring;
– recommendation systems for both new and prospective clients.
6. Logistics & Warehouses
The transportation and warehouse industry is data-driven and needs analysis of historical and real-time data performed by intelligent algorithms. So our team can help with:
- traffic management improvements
- warehouse optimization,
- route optimization (“travelling salesman” problem),
- developing optimal loading systems and utilization systems for vehicles;
AI can help insurance companies deliver high-quality service as it has done for major leaders in other industries such as Healthcare, Fintech, etc.
Our data science agency can help to:
- create a more personalized service;
- predict the repair costs from historical data;
- provide a selection of better investments based on risks, preferences, and spending patterns;
- improve claims analysis.
Farmers aim to maximize production and profits using innovative software and data collection and analysis. We can make the analysis of historical and real-time images & data collected from databases, satellites, drones, IoT sensors that can help to:
- increase the yield of farmlands;
- ensure serviceability of farm equipment;
- monitor fields conditions, irrigation, soil moisture, etc;
- predict weather conditions.
Nowadays AI helps to deploy effective cybersecurity technology and allows businesses to solve major cybersecurity challenges: cyberattack, financial loss, or brand reputation damage. We can help cybersecurity teams to:
- analyze patterns in user behaviors and respond to changing behavior;
- identify cyber vulnerabilities and irregularities in the network.
AI is already transforming the healthcare industry—helping patients and hospitals optimize costs and increase care delivery through actionable insights. We can help to:
- manage and analyze data to provide;
- improve preventive care;
- create personalized treatments;
- make optimization of scheduling and bed management;
- detect and analyze patient patterns and correlations for better decision making.
Technologies we leverage
Languages: Python, R, Scala, SQL, C++, etc.
Visualization: Power BI, Tableau, Qlik, Matplotlib, seaborn, ggplot2, plotly, Bokeh
DBMS: Relational (MS SQL, PostgreSQL, MySQL), Non-relational (MongoDB, CouchDB, Cassandra etc.), Distributed (Hadoop etc.)
ML Frameworks: Tensorflow, Scikit-learn, SciPy, etc.
Architectures: On-premise, cloud, hybrid
Algorithms: Supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction, anomaly detection, pattern search), ensembles, reinforcement learning
Fields: Natural Language Processing, Computer Vision, Recommendation systems, Tabular data analysis, Signal Processing
Cloud Platforms: Amazon Web Services, Google Cloud Platform, Microsoft Azure
Why Choosing Data Science UA?
A strong Machine Learning engineering team.
We are deeply integrated into the Ukrainian Data Science community and can find all required domain experts to come up with the best Big Data consulting services for ML;
We’ve worked with various industries before and can think out of the box when delivering Big Data consulting services.
Data Science UA can help with building and implementing ML solutions in different sectors. Besides, our Big Data consulting company is not afraid to ask questions and look for information to learn new industries/businesses better;
Our technical know-how in ML solutions development is solid.
We’ve designed ML software for many businesses. We value a T-shaped approach: each specialist should be an expert in a particular domain and have broad knowledge in other spheres. Thus, we are able to provide excellent Big Data consulting services, finding solutions to unique problems.
We offer flexible cooperation.
Data Science UA chooses the form of cooperation that will be the most suitable for the project’s needs and goals. You can work with us in team-extension-mode or on a project basis. We offer Big Data consulting services in cross-service projects (like consulting + data analysis & data science + recruitment or any other combination);
We use proprietary technologies.
Our Machine Learning software development company has worked in this domain for years and has developed and refined our own instruments. Now we can utilize some pre-built technologies to develop unique Machine Learning solutions tailored to the needs of your business;
We carry out R&D activities.
Our Big Data consulting company loves challenges and is eager to “do their homework”. We are an ML research company, keeping an eye on the new trends and looking for new ideas and approaches in Big Data consulting services to bolster our services and products.
There is also a list of organizations that certainly have Big Data:
- TV and Internet providers,
- mobile operators,
- banks and fintech companies,
- social media companies,
- some retailers,
- oil and gas companies,
- many factories and production companies.
The list goes on, but these are the examples of companies that most certainly have (and use) Big Data.
Now that you know whether you have Big Data or not, you can turn to data analysis. Data Science UA can help you with that. Refer to this page to find out more.
What is big data consulting?
Companies that have big data may often require help when starting to analyze it. Big data consultants can help in this case by inspecting the needs and problems, coming up with the most appropriate solution, and assisting in integrating the necessary tools and technologies.
How much does a big data consultant make for a business?
That depends on many factors: from the type of business to the amount of data and users. In the most modest case, big data consultants can save your business time and effort spent without big data technologies. But many companies receive huge profits reaching millions of dollars (https://www.kdnuggets.com/2014/12/top-10-big-data-companies-revenue.html) when utilizing big data correctly.
Can a data scientist work as a consultant?
Yes, if they have relevant domain knowledge and big data skills. In this case, they will be able to identify your business problems, find the best solution, and create the most appropriate plan of action.