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Enterprise Data Warehousing

At DPS we help you boost your analytics with a data platform designed to support emerging cloud and on-premises Enterprise Data Warehouse solutions.

All your data will be accessible in a timely, dependable, secure, and cost-effective manner. DPS’ cloud and on-premises data warehouse satisfy the requirements of today’s businesses, their clients and business partners.

We apply big data and advanced algorithms to your business problems in order to yield a solution that is measurably better than before. By identifying, sizing, prioritizing, and phasing all applicable use cases, businesses create an analytics strategy that generates value.

Simplify Analytics For Thousands Of Concurrent Users On Enormous Volumes Of Data Without Sacrificing Speed, Cost Or Security

An enterprise data warehouse (EDW) is a relational data warehouse that stores a company’s business data, such as customer information. Data analytics, which can lead to actionable insights, are made possible by an EDW. EDWs, collect and aggregate data from a variety of sources, acting as a central repository for most or all business data to allow for easy access and analysis.

Advantages Of Enterprise Data Warehouse

A system of “extract, transform, and load” (ETL) is frequently used to create a high-quality EDW. The popularity of ETL can be attributed to its ability to successfully develop and operate an enterprise data warehouse. However, as data volumes increased in the 2000s, a trend evolved to use databases for more scalable data integration, resulting to “ELT,” meaning the data is “Extracted (from source applications), Loaded (into the EDW), and then Transformed” data (within the EDW).

An EDW, as a consolidated repository for all of an organization’s data, improves availability and access to meaningful, contextual cross-organizational data, allowing for more comprehensive insights and smarter decision-making. This translates to higher return-on-investment (ROI) and increased corporate growth through faster-to-market action. When data is structured in a systemic, automated manner, organisations are more likely to be well-positioned for future growth.

Components Of An Enterprise Data Warehouse

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Data sources from operational and transactional systems (ERP, CRM, finance apps, IoT devices, mobile and online systems).

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A staging area for data cleansing and consolidation.

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Data is made available for analytics (querying, reporting) and sharing through a presentation or access space.

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A number of data tool integrations or APIs are available (BI software, ingestion and ETL tools, etc.)

Key Features

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Self-service provisioning & administration

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Proven at unprecedented scale & volume

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All data types, including real-time

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Query & optimization tools

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Integrated analytics across the data lifecycle

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Data visualization

Cloud Computing Is Cost-Effective And Easy To Scale Up And Down, Whereas On-Premises Data Centres, Allow You To Have Full Control Over Your Infrastructure

On-Premisis Data Warehouse Solutions

Utilize your existing infrastructure investments or use DPS’s purpose-built system to reduce latency and take advantage of on-premises data density. It’s important to note that on-premises EDWs are still preferred by healthcare organisations, as well as banks and insurance companies, because of the control they have over them. We will help your businesses set up an on-premises data warehouse solution that repeatedly builds new features and fixes bugs using agile approaches.

To help you set up a system and get going with one, we will install test instances on your own commodity hardware, run benchmarks to try them out, share the best ones with your management, buy the appropriate licenses and eventually deploy them.

On-Premisis Data Warehouse Solutions

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Support for some legacy systems (including customizability)

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Convenient access to the system's technical details

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Ease of control over physical data centres.

On-Premises Data Warehouse Use Cases

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Hospitals

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Bank

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Manufacturing and logistics

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Applications where data is proprietary and mostly consumed or accessed inside the organization

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Organizations with accessibility issues

An On-Premisis Data Warehouse

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Data center single tenancy (for compliance)

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Customizable hardware, purpose-built systems

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Large, regular infrastructural investments

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Complete data visibility and control

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Highly secure data encryption

Cloud Data Warehouse Solutions

The big advantage to a cloud-based solution is that, as a managed solution, tasks like sharding, replication, and scaling are done for you — with many even happening automatically, in the background! You also have fixed costs. There is no additional outlay for hardware, nor variable costs when something fails or needs to be upgraded.

Similar to on-prem solutions, cloud-based solutions will still, more than likely, require you to implement connectors, database schemas and streaming or ingestion mechanisms. However, it’s hands off with a lot of the routine maintenance and scaling activities and this alone can save you significant time and cost.

Cloud-based EDW Solutions Features

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No upfront requirement for hardware outlay

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Ability to massively autoscale

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Connectors for most major ETLs, data stores, and databases

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Technical support and maintenance, bundled in

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Highly secure data encryption

Cloud-based EDW Use Cases

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Any product or company building a data infrastructure from scratch, where there are no legacy systems to accommodate.

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Any product or company building a data infrastructure around fairly standard components.

A Cloud Data Warehouse

Utilize Your Complete Data

With instant access to a single trustworthy source for all your data, you can make data-driven management decisions.

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Cloud storage with near-unlimited capacity and 2-3x compression at a modest cost.

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A single copy of your data that is instantly accessible from anywhere.

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Geospatial data and analysis are supported natively.

Security, Governance & Privacy

Stay secure while giving authorised individuals controlled access.

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At rest and in transit, data is automatically encrypted.

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Masking and tokenization of dynamic data.

Fast and Easy SQL Analytics

With dedicated compute resources for each user and workload, you can avoid bottlenecks and service outages.

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To meet demand, quickly provision computing clusters varying in size from extra-small to 6XL.

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For near-unlimited concurrency, use multi-cluster computing resources.

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Optimized direct connectors for popular BI and Analytics tools

Managed Service

DPS simplifies data warehouse administration and maintenance and is designed primarily for a smooth cross-cloud experience.

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Caching, planning, parsing, and optimization of queries are all automated.

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Data replication across clouds for global data access.

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There will be no scheduled downtime due to automatic updates.