Amazon SageMaker
Amazon EMR
Azure Machine Learning
Azure HD Insight
Azure Data Factory
Power Bi
Within a subscription fee, you carry out data analysis on a fully customized cloud analytics platform built and maintained by Sneak Peek Tech.
Analytics Partner
Time-Saving Automation
We set up automated data management and governance processes and implement self-service BI to ensure you can easily create ad hoc reports without any coding skills, and your IT team doesn’t have to manage data manually.
Easy-To-Read Reports
We use various data visualization techniques to highlight the most important analytics insights in each report and make them easy to scan at one glance.
Reliable Insights due to Trustworthy Data
We consolidate your disparate data sources into a DWH to serve as a single point of truth for enterprise-wide analytics. Our robust ETL processes will guarantee your data is always accurate, consistent, and complete to facilitate dependable analytics.
Value-Focused Data Analytics
As an expert analytics consultancy, we don’t simply build reports — our goal is to help you fully utilize the potential of your analytics solution and discover new optimization opportunities hidden in your data (e.g., for operational cost reduction, productivity improvements).
Flexible Service Approaches
Analytics as a Service (AaaS)
Within a subscription fee, you carry out data analysis on a fully customized cloud analytics platform built and maintained by Sneak Peek Tech.
Managed Data Analysis
Data Analytics Consulting
Data Analytics Implementation
Your data analytics solution may include such elements as DWH, OLAP cubes, data visualization, data science, big data components etc.
Data Analytics Modernization
Data Management Services
Automation to Advanced Data Analytics
Data Integration & Data Warehousing
- Extract, transform, load (ETL) or extract, load, transform (ELT) design and implementation.
- Data governance (data security, quality, availability, etc.) implementation.
- Data warehouse and data marts design and implementation.
Big Data
- Big data infrastructure setup and support.
- Big data quality and security management.
- Big data capture, analysis and reporting.
Data Science
- Data preparation and management.
- Development and tuning of machine learning (ML) (including deep learning) models.
- Development and tuning of data mining models.
- Designing and implanting AI solutions.
- Image analysis software development.
Business Intelligence
- Business intelligence and data analytics infrastructure design and implementation.
- Ad hoc and scheduled analytics querying and reporting.
- Natural language user interface.
Artificial Intelligence
- Data gathering and cleansing for ML model training.
- ML modeling.
- Development of software modules that will use ML output.
Data Visualization
- Interactive dashboarding.
- Custom and pre-built visuals.
- Multiple visualization techniques (symbol maps, line charts, bar charts, pie charts, etc.)
Get in Touch with Us
Top 6 Data Analytics Tools for Comparison
Power BI
CATEGORY
BI and data visualization tools.
DESCRIPTION
A recognized leader (Gartner, Forrester, IDC) among self-service data analysis software. Power BI comprises a set of products – Power BI Desktop, Power BI service, Power BI Mobile, Power BI Report Server, Power BI Embedded. 100+ native data source connectors, multi-language support, AI-driven data preparation and analysis (including big data), pre-built and custom visuals, interactive visualization and dashboarding, intuitive interface, enhanced security.
Azure Data Factory
CATEGORY
Data integration tools.
DESCRIPTION
An Azure-based solution for ingesting, preparing and transforming data at scale. 90+ built-in maintenance-free connectors, ETL/ELT code-free processes supported by Apache Spark, easy migration of SQL Server Integration Services (SSIS) workloads, on-demand scaling, pay-as-you-go pricing model.
Azure HDInsight
CATEGORY
Big data tools.
DESCRIPTION
An Azure service for big data analytics with open-source frameworks and languages such as Hadoop, Apache Spark, Apache Hive, Apache Kafka, Apache Storm, R, and more. Integrations with BI tools (Power BI, Excel, SQL Server Reporting Services, etc.) and Azure data storage and analytics services (Data Lake Storage, Azure Blob Storage, Azure Cosmos DB, Data Factory, Azure Synapse Analytics, etc.). Data encryption, multi-user support, role-based access control.
Azure Machine Learning
CATEGORY
Machine learning (ML) tools.
DESCRIPTION
An enterprise-grade machine learning service for building, training, and deploying ML models fast. Supports open-source frameworks and languages for ML development (MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R). Automated ML development with built-in feature engineering, algorithm selection, hyperparameter sweeping, etc. Streamlined ML development life cycle with MLOps capabilities. Data encryption, built-in granular role-based access control, built-in identity authentication.
Amazon EMR (Amazon Elastic MapReduce)
CATEGORY
Big data tools.
DESCRIPTION
A big data platform for processing and analyzing large data volumes with open-source tools (Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto). Easy provisioning, scaling, and reconfiguring of clusters, manual/automatic capacity up- and downscaling. Secure and low-cost data storage enabled by integration with Amazon EC2 Spot, Amazon EC2 Reserved Instance, and Amazon S3.
Amazon SageMaker
CATEGORY
Machine learning (ML) tools.
DESCRIPTION
A leader in Gartner’s Magic Quadrant for Cloud AI Developer Services, Amazon SageMaker is a fully managed service for the entire machine learning workflow. Supervised and unsupervised reinforcement learning algorithms. Optimized for working with major ML frameworks (TensorFlow, Apache MXNet, PyTorch, Chainer, Keras, etc.). Automatic building, training and tuning of ML models with full visibility and control with Amazon SageMaker Autopilot. High performance and on-demand pricing.