Sound Familiar?
Five Signs Your Data Has Outgrown Its Platform
The monthly reports arrive a day late because the overnight loads ran long again. Sales data sits in one system, finance in another, and the AI pilot is still waiting for access. A cloud data platform brings that data into one store on AWS or Azure, with a named owner and access rules for each dataset, where reports, analytics and AI all read from the same source. Signisys, an IT services company in Noida, helps businesses across Delhi NCR and India build cloud data platforms on AWS and Azure.
Where It Applies
Six Data Platform Problems and What Fixes Them
Find the problem closest to yours, what it puts at risk and what fixes it.
The Risk
Another hardware purchase sized for peak.
What Reduces It
Cloud storage and compute sized separately.
The Risk
Decisions made on yesterday’s numbers.
What Reduces It
Monitored pipelines with alerts.
The Risk
Test and live setups that slowly stop matching.
What Reduces It
The platform defined as code.
ExploreInfrastructure as Code (IaC) and Configuration Automation
The Risk
Pilots that stall for weeks.
What Reduces It
A catalog with owners and AI rules.
The Risk
Salary or customer data seen by the wrong people.
What Reduces It
Access by table, column and row.
The Risk
Lost data that reports depend on.
What Reduces It
Tested backup and recovery.
Why Now
When Your Data Platform Needs a Decision
Four moments when the way you store and serve data deserves a fresh look.
The Reporting Hardware Is Due for Renewal
Replacing the database servers means paying for peak capacity for years to come.
The Board Asks for an AI Plan
AI needs governed, well-described data, and today that data is scattered across systems.
A New System Adds a Flood of Data
A new ERP, CRM or IoT feed adds more data than the current setup was built for.
An Audit Asks Who Saw Customer Data
Nobody can show who accessed sensitive data, or when.
The Outcomes
What Changes With a Well-Run Cloud Data Platform
Five changes to look for once your data lives on one governed platform, and how to check each one.
Our Approach
How We’d Approach Your Cloud Data Platform
We start with the data and reports you have, agree one platform design and move subject areas across in stages, with access rules set before data arrives.
Assess
Review Data, Loads and Access We look at your data sources, volumes, loads, reports, costs and who can see what, and rank what needs attention first.
You receive Data platform risks and options ranked by urgency. The Data Platform Review covers this step.
Plan
Agree the Platform Design We help choose the cloud services, storage layout, pipeline approach and access model that fit your data and team.
You receive A platform design and move plan your team reviews and owns.
Implement
Build and Move in Stages We help set up the platform from written code, so it can be rebuilt the same way each time, set up pipelines and move one subject area at a time, checking each report against the old numbers.
You receive Subject areas live on the platform with reports matched.
Govern
Set Owners and Access Rules We help name an owner for each dataset, set access by table, column and row and agree which data AI can use.
You receive Data owners, access rules and an AI data policy in place.
Optimize and Manage
Keep Loads Reliable and Costs Lean Where ongoing support is agreed, we watch pipelines, tune compute and report on cost, load times and access.
You receive Platform cost, load and access reports on an agreed schedule.
Want to understand how we deliver? Explore our Technology Delivery Methodology
Services
Services to Plan, Implement and Support Your Environment
The services behind the approach. Engagements include only what you need.
Not sure where to start?
Tell us about your goals and we will recommend the right mix of services for your business.
How It All Works Together
How a Cloud Data Platform Works
Pipelines bring data from business systems into one governed store, where reports, analytics and AI read from the same source under the same access rules.
One Data Standard
- Owners, access rules, naming, retention and AI use, agreed with your data lead and security owner.
- Reviewed when a new source joins and each year.
Check Your Data Platform
Business Systems
ERP, CRM, finance, files and device feeds.
Feed
Monitored Pipelines
Loads that run on schedule and alert their owner on failure.
Load
Governed Data Store
One cataloged store on AWS or Azure with access by table, column and row.
Serve
Reports, Analytics and AI
Dashboards, analysts and AI models reading the same data.
Load, cost and access reports update the data standard
A Load Fails or Runs Late
The pipeline alerts the dataset owner.
Owner notified
Load Fixed and Rerun
Reports refresh once the data is complete.
Works With What You Have
- Connects to existing systems without replacing them.
- Moves reports across one subject area at a time.
Security and Governance
- Access by table, column and row.
- Every access to sensitive data logged.
- Rules for which data AI can use.
What Is Covered
- Data platforms on AWS and Azure.
- Pipelines, storage, access, catalog, reporting and cost controls.
Solutions
Solutions That Support Your Business Objectives
The solutions that address the gaps above.
Technologies
Tools Behind a Well-Run Cloud Data Platform
Each part below covers one job in running a data platform, from the standard to the cost report. If a tool you already pay for covers a part, we use it first.
Your First Step
Start with a Data Platform Review
We look at your data sources, volumes, loads, reports, costs and access on your current setup or on AWS and Azure. Nothing is changed during the review. You get data platform risks ranked by urgency, a recommended platform design and a plan for moving subject areas across in stages. The findings are yours to keep.
- We walk you through the findings on a call.
- Then it’s your decision, with no obligation to go further.
Scope
- Data sources, warehouse and pipelines
- Reporting and AI requirements
You Provide
- A list of key systems and data sources
- Details of current loads and reports
- Time with your data or BI lead
You Receive
- A recommended platform direction
- Data sources ranked by business value
- A first release plan and rough costs
Cost and Timing
- No charge, with a fixed scope
- Timing depends on the number of data sources and reports involved, so talk to us
Keep Reading
Explore Insights and Resources
FAQs
Cloud Data Platform: Frequently Asked Questions
What is a cloud data platform?
A cloud data platform is a set of cloud services that brings data from business systems into one governed store, where reports, analytics and AI read from the same source. It covers pipelines that move data, storage, compute (the processing power that runs queries), a data catalog (a searchable list of every dataset and its owner) and access controls.
Why move a data warehouse to the cloud?
In the cloud, storage and compute are sized and paid for separately, so you stop buying hardware for peak demand. You can also add new data sources and AI services without a new hardware project.
Does a cloud data platform need a data lake or a data warehouse?
Many platforms use both: a lake to hold raw files cheaply and a warehouse for fast, structured reporting. The review looks at your data types and reports before recommending a layout. Our Integrate Business Data Across Systems use case explains each term.
Should we build on AWS or Azure?
Either can host a cloud data platform. Azure fits teams already using Power BI and Microsoft 365, and AWS fits teams whose applications already run there. The review looks at where your data and skills are today before recommending one.
What is Microsoft Fabric?
The Microsoft Fabric overview describes it as an analytics platform delivered as software as a service, a ready-made online service with nothing to install. It includes Data Factory for data integration, data engineering, a data warehouse, databases, Real-Time Intelligence, data science and Power BI, all working over one logical data lake called OneLake.
How do you control access to data on AWS?
The AWS Lake Formation guide describes a single place to set access rules for data in an Amazon S3 data lake (S3 is AWS’s file storage service), down to database, table, column, row and cell level. Access is logged through AWS CloudTrail, so you can see which users or roles tried to access which data, with which services, and when.
Can we keep our existing reports?
Yes. Reports are moved one subject area at a time and checked against the old numbers before the old source is retired. Power BI reports can point to the new platform once the data matches.
How long does it take to see results?
One subject area, such as sales or finance, goes live first, so reports improve before the whole move is done. Timing depends on how many sources and reports there are, which the review estimates.
Do we have to move everything at once?
No. We move one subject area at a time, run old and new side by side until the numbers match and then retire the old source. Each step is small enough to check and reverse.
How do you keep cloud data platform costs under control?
Size compute to real query load, pause or scale down what sits idle, keep older data on cheaper storage and break costs down by team. Monthly reports show where spend is growing.
How do you make data ready for AI?
Catalog each dataset, name an owner, check its quality and agree which data AI may use. Our Improve Data Quality for Analytics and AI use case covers the quality side.
How do you protect sensitive data on the platform?
Limit access by table, column and row, hide fields such as salaries and ID numbers from people who do not need them, encrypt data and log every access. Access is reviewed on a schedule, and anything no longer needed is removed.
What happens when a data load fails?
The pipeline alerts the dataset owner, who fixes and reruns the load. Reports refresh once the data is complete, so people do not see half-loaded numbers.
Does the platform need its own backup?
Yes. Cloud storage keeps data available, but deleted or corrupted data still needs a tested way back. We plan backup and recovery for the platform along with the rest of your systems.
Who should own the data on the platform?
Each subject area needs a named business owner who decides who gets access and what the data means. A data lead runs the platform itself.
How is this different from integrating business data?
Integrating business data is about connecting systems so data moves between them. This page is about building and running the cloud platform where that data is stored, governed and analyzed. Our Integrate Business Data Across Systems use case covers the first.
Which platforms do you work with?
We work with AWS and Microsoft as a Technology Partner, building cloud data platforms on AWS and Azure, including Microsoft Fabric and Power BI.
What happens in the Data Platform Review, and what does it need?
The Data Platform Review looks at your data sources, volumes, loads, reports, costs and access, and ranks what needs attention first. It needs read-only access to your current data setup, a list of key reports and time with your data lead. We walk you through the findings on a call. Signisys is based in Noida and works with businesses in Delhi NCR and across India; book through this page or call +91 7669 966 966. A Signisys specialist responds within 1 business day, and there is no obligation to go further.
Discuss a Project
Make Your Data AI-Ready
A free review outlines a cloud data platform for your sources, reports and AI plans, with first steps to take.
What happens next?
- We Get in TouchA technology specialist contacts you within 1 business day.
- We Understand Your NeedsWe arrange a 60-minute discovery session to understand your requirements.
- We Assess Your EnvironmentWe evaluate your needs, identify opportunities and recommend the right approach.
- We Define the Way ForwardWe present a tailored proposal with clear scope, deliverables and expected outcomes.
Existing Clients
Already Working with Signisys?
For questions about an ongoing engagement, contact your Signisys account team, or reach us directly by phone or email.
What happens next?
- We Acknowledge Your RequestYour account team responds within 1 business day.
- We Establish OwnershipWe understand your requirement and connect you with the right team.
- We Work on Your RequestThe relevant specialist coordinates with you to address your requirement.
- We Ensure ClosureWe follow through, confirm resolution and keep you informed.
Call Us
+91 7669 966 966Email Us
connect@signisys.comResponse within 1 business day
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