Big Data Consulting Services
Analyze Large Datasets and Boost Your Operational Efficiency with Big Data Consulting services
Our Big Data Consulting company with the help of advanced technologies and tools like Delta Lakes, Spark, Hadoop and Cloud technologies will process your datasets, drive business insights from it, and suggest the most effective strategy of data culture implementation. We provide companies with reliable big data analytics consulting and a fast implementation process.
Big Data Consulting Services & Implementation
Big data consulting is a sophisticated service based on the process of examining vast amounts of data. Our goal is to uncover useful business-wise information and hidden correlations and connections within it. It has been designed to help organizations in making more optimal decisions, thanks to insightful analysis. Big data strategy implementation, consulting and services helps your company to grow faster and improve the decision-making process.
The benefits of big data technologies can never be overrated. You can think of any field of doing business on a large scale, and we bet big data might be applied to it with ease. To name some of the critical benefits, let’s say it’s of significant importance for:
- New business opportunities (new niches, new product development, new target audience)
- Cheaper data storage (store data in raw format and query directly files)
- More effective marketing (more accurate marketing strategy, better optimization)
- Better customer service (customer churn prediction, improved communication)
- Improved operational efficiency (quicker and more precise decision-making process)
Big data consulting services, along with business intelligence services, are your guides through almost unimaginable amounts of data.
Addepto Big Data Services include:
Application streaming is a form of on-demand software distribution. We carefully choose the most important portions of an application’s code which is being applied on the end user’s computer. The code files and delivers over the network accordingly to actions performed by a particular user. Applications are run by a virtual machine on a central server which is separate from the local system.
Data Lakes and Delta Lakes
Data lake is a system of all company’s stored data. It can include structured data, semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). Delta Lake acts as an additional storage layer that brings reliability to your data lakes. It uses versioned Parquet files to store data in cloud storage.
Big Data Processing
Big Data Processing is a set of techniques that enable an organization to use the full potential of its data. The process includes: Analysis using operational memory (RAM memory); NoSQL databases; Columnar database that reduces the number of reading data items during query processing; Graph databases and analytical tools; Extracting, Transformation and Loading (ETL) operations; Processing big data with interactive data querying; Predictive analytics.
Data integration is the combination of business and technical processes used to integrate data from various data systems and sources into meaningful and valuable information. A complete data integration solution delivers trusted data from various sources to support a business users and decision makers.
RELATED CASE STUDIES
Big Data and Analytics in Mobile Gaming
We helped a mobile gaming company to increase IAP, LTV, and retention using artificial intelligence-driven technology. We implemented analytics in mobile gaming, transformed big data into an appropriate format, implemented fraud detection, and applied machine learning-based tools enabling our client to predict customer lifetime value (CLV), as well as customer churn. Through Modern Data Warehouse and BI implementation, we achieved data monetization.
Embedded Analytics in a Saas Application
We developed an analytics system with self-service interactive dashboards and reports to analyze customers’ data and improve customer experience (customer 360). Additionally, we implemented a customized machine learning system for customer churn prediction, sales predictions, and recommendation systems which results were visualized using BI. We created a tailor-made data integration solution for both structured data and Big Data sources, combined together in a data warehouse.
Big data ecosystem can become one of your company’s most valuable resources. However, it won’t be able to play its role unless it is identified, gathered, managed and analyzed. To deal with this challenge you need a reliable big data analytics strategy.
1) Identifying current and potential data sources
It is not enough to start with already existing data, to use full potential of big data you have to identify additional data sources that can be used to collect structured & unstructured data. After that, our team will prioritize and evaluate them during this stage.
2) Identifying current and potential data sources
To reduce sotrage costs data is stored in so-called data or delta lakes. A data lake is a repository for storing both structured and unstructured raw and processed data files. Unlike a data warehouse, a data lakes implies a flat architecture for storing the data in its source format. It is possible to build and deploy data lakes using cloud or on-premises infrastructures using dedicated tools such as Hadoop, S3, GCS or Azure Data Lake.
3) Connecting data sources to your clients
After deciding on data sources and storage, we connect them to the needs of your clients. Let’s say, if you are leading the retail chain, we can collect the data with the help of digital coupons. A customer gets a coupon for a discount and is happy to visit your place. In turn, you also get what you want.
4) Incorporating new data hubs
The next step is incorporating new data hubs one by one. This is a gradual process. In this way, you will have enough time to adjust your operations and understand how to use the data.
5) Connecting the clients’ data to your company’s processes
Every data set you gather provides your company with an opportunity to improve the your services or products. Therefore, data-driven decisions should be present at the company at all levels: product development, pricing, marketing, operations and HR etc.
Testing, measuring and learning — are crucial in the big data analytics process. When collecting another data set, we will test the related assumptions to make the right decision on how to move forward. Big data visualization tools and techniques are important at this stage too.