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Anblicks DataOps

Detect, Resolve and Prevent
Data Downtime

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As data becomes increasingly important to today’s businesses, ensuring its Quality and Reliability has never been more critical. High-quality data is vital for any organization’s success, from building new products to driving accurate decision-making to powering AI/ML use cases.

Our DataOps offering provides an end-to-end solution to enhance data accuracy, timeliness, and quality while minimizing data platform spend. Leveraging the
”EDGE” platform, this comprehensive managed service helps organizations build a data-driven culture by improving data trust and reliability.

Graph image - Anblicks DataOps - Detect, Resolve and Prevent Data Downtime

Why Anblicks DataOps

Critical for Business Success

High-quality data is essential for creating new products, making accurate decisions, and powering AI/ML applications.

Addressing Failure Risk

According to Gartner, by 2025, 80% of organizations aiming to scale digital business will fail due to not adopting a modern approach to DataOps.

Enhances Data Reliability

Ensures data accuracy and timeliness, which are crucial for business operations and strategy.

Minimizes Data Platform Spend

Streamlines data operations to reduce costs while enhancing data quality and reliability.

DataOps Features


Enterprise DataOps Platform

Utilizes a comprehensive platform to manage data workflows efficiently.


Automated Metadata Extraction

Configures automated metadata extraction and end-to-end data lineage for explainability.


Incident Management Workflow

Implements automated workflows to flag and manage data incidents, ensuring minimal downtime.


Data Governance and Catalog

Features data catalog, glossary terms, and profiling tools to enhance data findability and quality.

Offerings & Solution Outcomes

Assess & Adopt - big banner image

Up to 4 Weeks


Data Ops Operating Model, Transition & Playbook

  • Analyze current Data Estate​.
  • Define and Assess current state DataOps Op Model​.
  • Identify Stakeholder(s).
  • Identify Roles & Responsibilities​.
  • Identify Corporate Data Domain(s)​.
  • Identify & Prioritize Critical Data Elements (CDE)
under each Domain.​
  • Document & Prioritize current Data Trust, Data
Quality & Data Reliability challenges.
  • Document Data Asset Service Level Agreements (SLA’s)​.
  • Document Run-Books​.
  • Document L1.5, L2 and L3 Incident Management, Problem Management and SLA’s.
  • Document Communication & Escalation model.
  • Document prescriptive DataOps 24*7 coverage.
  • Define Prescriptive Target State Operating Model Playbook​.
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Up to 5 Weeks


Enterprise DataOps
using “EDGE” platform​

  • Implement and configure “EDGE” platform​.​
  • Define and configure Data Domains (e.g. Sales, Finance etc.).
  • Define and configure Sub-Domain (e.g. Order, Invoice etc.) for each data domain.
  • Define and configure Critical Data Elements/Assets under Sub-Domain.
  • Configure and Perform automated metadata extraction from the identified data source​.
  • Configure end to end “Data Lineage” for explainability and impact analysis​.
Snippets image - Accelerate - Offerings & Solution Outcomes

Up to 6 Weeks


Minimize Data Downtime

  • Steady State DataOps​​.
  • Monitor KPIs and SLAs.
  • Configure Weekly Status Reporting​.
  • Run Book Automation​.
  • Configuring “Incident Manager Workflow” in EDGE platform to flag Data Assets as being in an unhealthy state​=
  • Configure “Data Observability” in EDGE platform with assertions to minimize “Data Downtime” and maximize “Data Quality”​.
  • Data Freshness assertions​.
  • Data Volume assertions​.
  • Custom SQL assertion.
  • Column assertion​.
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Up to 12 Weeks


Enterprise Data Governance using “EDGE” platform​

  • Define Data Semantics & Glossary terms for the Critical Data Elements/Assets.​
  • Configure Data Catalog and Search feature for findability.
  • Co-create and assist “Data Custodians” to define technical metadata to Critical Data Elements/Assets​.
  • Co-create and assist “Data Stewards” to define business glossary & data dictionary to critical data elements/assets.​
  • Co-create and assist “Privacy Stewards” to define PII tags and access policies.​
  • Configure “Data Profiler” feature and functionality to determine Data Quality issues​.
  • Implement FinOps.

Benefits of DataOps

Reduced Incidents and Increased Stability

Improves DataOps stability and reduces incidents by 20-30% in the first year.

Cost Savings

Reduces cloud data platform spend by 20-25% in the first year.

Minimized Data Downtime

Enhances data trust, quality, and reliability, minimizing data downtime.

Competitive Advantage

Leverages high-quality data for better decision-making, improving competitive position and business outcomes.

Enhanced Revenue Opportunities

High-quality data assets drive better business outcomes & new revenue opportunities.

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