What we offer
Data analysis services cover a large gamut of operations that relate to collecting, processing, and presenting business information in a convenient format so that companies can leverage it as actionable insights in their strategic planning, decision-making, and performance optimization. As a data analysis company with over ten years of experience in data analytics, DICEUS meets our clients halfway through providing the following kinds of services.
Audit of data management/governance
Most organizations have some data management policy, but they may not be sure it is up to the mark. We perform a complete check of your firm’s procedure, gauge its efficiency, detect bottlenecks and pitfalls that impede its smooth employment, and pinpoint future risks likely to crop up if you follow the adopted data handling strategy.
Reports on audit and analytics results
The outcome of the auditing services provided by our specialists is a comprehensive report. This document lists systemic data issues, reveals incomplete data sets and siloed data, exposes data security gaps and barriers to data access, and identifies insufficient depth or width of data collection to enable our customers to institute corrective measures.
On-time delivery of results and recommendations
Knowing the field inside out, we do not only deliver the results of the IT data analysis conducted within the timeframe stipulated by the contract. Our experts also offer relevant and benchmarking-driven recommendations that will allow businesses to step up data quality, increase the efficiency of data governance, and support compliance adherence.
Guaranteed security of your data
When a business or personal data stored by the organization on-premises or in the cloud is compromised, the company may suffer substantial financial losses and severe reputational damage. Realizing the vital importance of data security, DICEUS employs exclusive protective measures while doing any tasks and jobs related to processing corporate data.
ETL, QA, and other data management services
The AI-powered data analysis solutions that we employ enable versatile operations with information. Our ETL (Extract, Transform, Load) tools are honed to gather data in various formats from multiple sources and unite it into a single database. In addition, QA services by DICEUS guarantee the consistency, durability, accuracy, and compatibility of the data we process.
Data warehouse (DWH) development
Having all data hoarded in disparate locations causes a problem with its efficient handling. We can bring it together under one roof of a data warehouse. It relies on top-notch back-end software, infrastructure, and security protocols and has a customizable and user-friendly dashboard at the front end, which turns the data processing routine into a cakewalk.
Efficient data analysis is the cornerstone of business success for enterprises in any industry. However, even for many large-scale brands (to say nothing of cash-strapped startups and small companies), investment in developing and managing analytics tools is an expenditure item far beyond their modest means.
By outsourcing such services to seasoned data analysis firms – and DICEUS is one of the leaders in the niche – businesses can streamline and facilitate data management and analytics. It is a surefire recipe for enhancing the efficiency of their workflow, expanding market reach, and stepping up customer satisfaction of the clientele.
Benefits of our data consulting
Organizations amass tons of client and internal data during their operation. Yet without a competent helping hand, they often struggle to turn this data into a corporate asset. The comprehensive data analytics and consulting services DICEUS provides will allow your company to become an efficient insight-driven brand. What makes us so sure?
How it works
An experienced team with solid competence in the field and the state-of-the-art tech stack to apply are the two vital summands of success in data analysis. However, no less critical is an adequately organized procedure for performing it. Vetted mavens of DICEUS have developed a universal roadmap that manifested its efficiency in numerous use cases.
What impacts your project duration
With the arrival of new data, its analytics can become a never-ending procedure. However, companies want to know how long the analysis of their available data will last. To give the exact timeframe, we need to know:
- Project requirements
- Anticipated deadlines
- Team size and roster
- Chosen platforms and tech stack
- Change requests
What affects your project costs
Modern entrepreneurs are calculating people who want to get all value for the money they pay for any service. We can announce the precise sum only if we are aware of the following:
- Harnessed technology
- Project scope and complexity
- The urgency of project completion
- The engagement model the customer prefers
- Current data condition
What we need from your side
An organization that commissions the job and forgets about the project expecting the outsourcer to do everything independently, can hardly hope to get a fast and high-quality outcome. Therefore, to achieve a satisfactory result for both parties involved, we need close cooperation from your side, which includes providing the following information.
- The project vision, goals, and roadmap (if they exist)
- High-level project requirements
- Available project documentation (software architecture, mockups, or any other papers)
- Project deadlines
- The client’s accessibility schedule (as a rule, several hours a week to hold requirements gathering sessions)
Our tech stack
Explore our case studies
Frequently asked questions
The process of working with data to obtain valuable insights will serve as a foundation for more knowledgeable decision-making. It involves collecting raw data from multiple sources, storing it in one virtual place (preferably a cloud-based data warehouse), applying various tools to examine it, and presenting the obtained results in an easy-to-understand format.
Four primary data analysis methods differ in their purpose. The descriptive method aims to reveal what happened in the past. The diagnostic method is called to explain why it happened. The predictive method maps out the developments that are likely to occur in the future. The prescriptive method offers the best course of actions to take.
Any digitally-driven endeavor is never a chump change issue; data analysis is no exception. Companies allocate from 2% to 6% of their budgets for data analytics, ranging from $10,000 to $100,000 annually for small and mid-size businesses. Many factors condition the final sum, the chief of which are the volume of data to analyze and the tech stack to employ.