The amount of data circulating today is growing exponentially. With almost 90% of it being created over the last 2 years. It comes from various sources thus making it difficult to identify, integrate and make sense of. But in order to succeed, businesses can’t afford to ignore the valuable information they have on their hands. They need to find a way to structure it and draw insights. Data analytics services offer an entirely new perspective on making informed business decisions by examining data sets, finding trends, and drawing conclusions by applying the latest technologies and software. Companies today are largely investing in data analytics consulting services and consulting to leverage valuable insights Talk to our expert Your Road to Intelligent Business Why Data Analytics as a Service Enable fast, data-driven decisions No need to wait until your data gets obsolete. Having access to data and being able to efficiently collaborate with it is key to a good decision-making and mitigating financial losses. Business Intelligence takes raw data and turns it into hard facts that help making the right decisions avoiding miscalculations and saving time and money. Having important business data on their hand can also help organizations to limit the losses in case the incident occurs. Own the data Be sure that you are in control of all the data assets created. Owning your data streamline operational efficiency, as you no longer need to use multiple information silos. Furthermore, self-service data analytics can also help with improving general business efficiency with predicting and averting certain events from happening, as well as improve internal processes, better engage workers and generally strengthen productivity. Footprint for AI If one day you plan to integrate some Machine Learning or Artificial Intelligence features to, for instance, increase your product evaluation, you need structured datasets and data warehouse consulting services (DWH services) that can make this happen. Personalized experience for your customers Building personalized brand experiences is a competitive advantage for any business. The foundation of this service offering is customer data. With implementing data strategy organizations will be able to offer a unique customer journey, tailored to specific needs of specific customers and nurture customer loyalty. Support your sales and marketing activities Data analytics services can be applied to produce forecasts and reports on service offerings, geographies, as well as offer 360-degree customer view, or collect third-party metrics. While reverse ETL can help deliver conversion and segmentation data to the marketing tools. Consequently, this enables sales and marketing team to test some hypothesis rapidly and analyze marketing leads. Let’s Talk Need more details?Let us assist you in maximizing your data potential by designing the right data engineering solution Talk to our expert Data Analytics Ecosystem Modern Data Architecture Consulting With our data architecture consulting service, we can quickly find and unify your data across various storage technologies and digital marketing platforms. And after careful analysis, present the solution. We already have a couple ready-to-use architecture blueprints to offer you universally established best practices and tools to design data lake or cloud data warehouse engineering services. Modern approach to data architecture strategy is combining all the possible data sets together, coming from different data bases, ML, application logs or from an existing data warehouse and joining it together into a data lake analytics, a central place where all the data of your company is being held and is accessible to everyone in a secure way and with proper permissions. Data Model Development Our data modeling services can help make your data more reliable, consistent by defining the model how the data should work. A good data model helps to properly store and access the data as needed. Our team performs data modeling taking into account all the requirements: technical, business, data requirements to come up with data modeling approach and implement it. Data Integration and ETL Pipelines After the architecture and the data model are defined, we need to integrate data. Data pipelines (ETL) is the process of extracting, transforming the data according to data models defined in the previous stage to share with the data warehouse (DWH) or other digital marketing tool or application. In case of reverse ETL, the data is being transferred out to digital marketing tools and CRM integrations. For all our clients we are using standardized stack and open-source tool Apache Airflow. This allows us to reuse integration components we have built in order to roll our quickly if the new tasks come up. Big Data and Cloud Engineering When the business grows, usually data grows with it. Implementation and management of Big Data and Cloud Engineering means getting the value out of the data as quickly as possible, and effective ways of storing and accessing the data. Data needs to be collected, stored, accessed in near-real time, and be available in a variety of formats. Since we are getting the data from various places, quite frequently the quality of the data can be questionable. Data cleansing improve data quality to make it usable for Business Intelligence (BI) and Machine Learning (ML). We are Operating in two clouds mostly AWS and GCP. But can work with other cloud systems as well (i.e., Azure, Snowflake). Business Intelligence As the previous steps are completed, we can use data for the actual business intelligence (BI) and value. At this stage we are building the reports and interactive dashboards with data visualization and charts. Whichever business can benefit from the most. We handle all the needed data preparation for these reports and all the advanced SQL. Once we build the dashboards, we can automate them as well. It means constant or even real-time updating. Once you open the dashboard, you can get up-to-date information. No need to wait or ask for someone do it manually. For this service we are covering a wide variety of BI tools – Looker, Data Studio, Quick Sight, Tableau, Power BI. Request Data Engineering Consultation Contact Us Why Cyber Craft Solutions Dynamic capacity We can dynamically scale up or scale down, to some extent but this means you don’t have to make an extended commitment. Dynamic team composition If at some point you need a specific profile or expertise, we should have it on board and ready to join your team in a completely transparent manner. Ready to start tomorrow Literally. This is not an exaggeration but something we are ready to commit to. Available blueprints within Cyber Craft DevOps stack We have some ready-to-use scripts that allow to deploy and deliver value fast. Domain knowledge We know the business and the nature behind your data. We have considerable experience in iGaming domain, as well as healthcare, retail and renewables and our domain knowledge and expertise keep growing. Industries we can provide for Our Data & Analytics experience spans across but is not limited to the following industries: iGaming Healthcare eCommerce Retail Financial More on the topic 10 Data Engineering Best Practices for Your Business Read more ➔ Data Engineering Concepts, Approaches, Data Pipeline, Data Warehouse Read more ➔ Preparing Your Dataset for Machine Learning on Data Warehouse Read more ➔ READ TESTIMONIALS OF OUR Clients They’re highly competent. They have passion around engineering and their management team. They’ve delivered work for us under extremely difficult circumstances. Head of Sportsbook Architecture Gambling Company They delivered an entire Sportsbook app with 35 people. We reduced our yearly costs by working with them. Ladbrokes Coral CEO We do not focus on any particular technology, we simply build the best-dedicated teams for our clients. Theo Schnitfink Founder of Cyber Craft Solutions They’re skilled in Agile. Without them, we wouldn’t have made nearly the progress we have with Agile. VirtualStock Vice-President Their desire to go the extra mile is a rare quality in third-party relationships. CEO Blexr Ltd Their desire to go the extra mile is a rare quality in third party relationships. BleXr CTO
