Bringing data quality and observability together: the ultimate stack to achieve healthy data

September 16, 2022

For most organizations today, data is their most important asset. Or, at the very least, it has the potential to be. However, in order to reap the full benefits, firms must properly manage their data. This management includes everything from data collection to data maintenance and analysis. A key result of managing data well is that its quality remains constant and does not deteriorate. 

In this blog, we will understand what data quality and observability are, and how we can bring them together to achieve healthy data on which organizations' decisions can rely. 

Content of the blog:

  1. What is Data Quality
  2. What is Data Observability
  3. Why is Data Observability Important
  4. Benefits of Data Observability
  5. Conclusion

What is Data Quality

Data quality determines whether or not data is appropriate for use in making trustworthy business choices. Measuring data quality is crucial to comprehend if you want to confidently use company data in operational and analytical applications. Only high-quality data can fuel correct analysis, which leads to reliable business choices.

There are 9 dimensions on which data quality relies.

  1. Data Observability 
  2. Rules engine based on SQL 
  3. When columns are added or removed from a schema. 
  4. Shapes - Typos & Formatting Errors 
  5. Duplicates - Fuzzy matching, identifying items that are similar but not identical 
  6. Outliers include anomalous records, clustering, time series, and categorical data. 
  7. Anomalies in pattern classification, cross-column, and parent/child relationships 
  8. Deltas for a certain column (s) 
  9. Reconciliation from source to destination

What is Data Observability

Modern businesses must monitor data across several tools and apps, but few have the visibility required to see how those tools and applications interact. Data observability may assist businesses in understanding, monitoring, and managing their data across the whole technology stack. 

The capacity to analyze, diagnose, and manage data health across numerous IT technologies across the data lifecycle is referred to as data observability. A data observability platform assists companies in detecting, triaging, and resolving real-time data issues by utilising telemetry data such as logs, metrics, and traces. Beyond monitoring, observability enables enterprises to increase security by tracing data transfer across diverse apps, servers, and tools. Companies may use data observability to simplify business data monitoring and control the internal health of their IT systems by examining outputs.

In short, data observability: 

  • Monitors the status of business data systems. 
  • Aids in diagnosing the whole data value chain
  • Enables large-scale data quality management 
  • Reduces data downtime 
  • Ensures quick access to reliable data

Why is data observability important? 

Traditional data quality focuses on resolving data problems reactively. It may miss the whole data path across the company while scanning the data sets. Data observability, on the other hand, enables the diagnosis of the whole data value chain. It monitors the health of business data systems proactively, alerting you about any problems in advance.

Benefits of Data Observability

Although there are many advantages of Data Observability, down below we have jotted them down to the four most important ones.

  1. Creating a clear data quality methodology to bring data together and build a shared understanding for better insights and choices. 
  2. Improving data consistency across systems and processes for effective data integration 
  3. Clearly establishing data-related rules and processes to achieve homogeneity across the whole company 
  4. Outlining roles and duties in data management and data access for stakeholders' clarity Improving compliance by enabling quicker data incident response and resolution 

On the other hand, inadequate data governance can stymie regulatory compliance activities, causing organisations to struggle to comply with new data privacy and protection requirements.

What is the difference between data observability and data quality? 

On numerous critical aspects, data observability varies from standard data quality. Data observability enables DataOps and data engineers to track the course of data, go upstream from the point of failure, identify the main cause, and assist in resolving it at the source.

  • Data Quality is defined as trustworthy reporting and compliance [downstream], whereas Data Observability is defined as anomaly detection, pipeline monitoring, and data integration [upstream].
  • The importance of data quality is repairing data mistakes whereas Data Observability reduces the cost of rework, remediation, and data outage by watching data, data pipelines, and event streams.
  • Data Quality deals with finding 'known' concerns whereas detecting 'unknown' difficulties is dealt with by data observability.
  • Data Quality employs human static rules and measurements, whereas data observability uses machine learning-generated adaptive rules and metrics.

How to Put Data Observability with Data Quality into Practice

If you already use data quality tools, consider if they truly enable you to achieve end-to-end quality. Most tools offer relatively limited automation and scalability. Their assistance with root cause investigation and processes is also insufficient. A mature approach to rules uses ML to make them more understandable and shared. As a consequence, data quality operators no longer have to rewrite rules when data travels between environments. They can then manage migration and scaling more effectively. The simplicity with which rules may be shared across multiple systems frees business users from having to worry about coding languages.

The 5-step procedure for improving predictive data quality and observability:

Step1: Connect and scan a diverse set of data sources and processes, including files and streaming data.

Step2: Profiling statistics, including hidden associations and time series analysis, are displayed for each data collection, table, and column.

Step3: Using automated technical rules, create generic DataOps and statistical controls to discover unexpected issues and expand your data quality activities.

Step4: Create adaptable, non-proprietary, explainable, and shareable domain-specific controls using automated and bespoke business rules.

Step5: Integrate data quality procedures into mission-critical business activities. When data quality scores drop, send warnings to the appropriate data owners to rectify errors as soon as possible.


Allowing business users to identify and assign quality concerns means that data quality activities are coordinated across the company rather than being restricted to a small team. Using metadata to complement this technique provides the correct context for quality concerns for impact evaluation. 

A unified data management strategy (keeping data quality and operability together) integrates data quality, observability, catalog, governance, and lineage. It enables you to consolidate and automate data quality operations in order to provide a comprehensive approach to data management and get the most out of your data and analytics expenditures.

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Cloud GPUs vs On Premises GPUs

Cloud GPUs are typically more powerful than on-premises GPU instances. The cost of renting a cloud GPU is generally lower than the cost of purchasing an on-premise GPU. 

Cloud platforms offer fast access to high performance compute and deep learning algorithms, which makes it simpler to start using machine learning models and get early insights into your data. 

Cloud GPUs are better for machine learning because they have lower latency, which is important because the time it takes a neural network to learn from data affects its accuracy. Furthermore, cloud GPUs allow users to take advantage of large-scale training datasets without having to build and maintain their own infrastructure.

On Premises GPUs are better for machine learning if you need high performance or require access to cutting-edge technologies not available in the public cloud. For example, on-premises hardware can be used for deep learning applications that require high memory bandwidth and low latency.

Cloud GPUs: Cloud GPUs are remote data centers where you can rent unused GPU resources. This allows you to run your models on a massive scale, without having to install and manage a local machine learning cluster.

Lower TCO: Cloud GPUs require no upfront investment, making them ideal for companies that are looking to reduce their overall capital expenses. Furthermore, the cost of maintenance and upgrades is also low since it takes place in the cloud rather than on-premises.

Scalability & Flexibility: With cloud-based GPU resources, businesses can scale up or down as needed without any penalty. This ensures that they have the resources they need when demand spikes but also saves them money when there is little or no demand for those resources at all times.

Enhanced Capacity Planning Capabilities: Cloud GPU platforms allow businesses to better plan for future demands by providing estimates of how much processing power will be required in the next 12 months and beyond based on past data points such as workloads run and successes achieved with similar models/algorithms etc... 

Security & Compliance : Since cloud GPUs reside in a remote datacenter separate from your business' core systems, you are ensured peace of mind when it comes to security and compliance matters (eigenvector scanning / firewalls / SELinux etc...) 

Reduced Total Cost Of Ownership (TCO) over time due to pay-as-you-go pricing model which allows you only spend what you actually use vs traditional software licensing models where significant upfront investments are made.

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Impact of the Strong Dollar: Cloud Costs Increasing, Be Indian Buy Indian

Indian SMEs and startups are feeling the effects of the high dollar. These businesses use hyperscalers(MNC Cloud) who cannot modify their rates to account for the changing exchange rate. For certain companies, even a little shift in the currency rate may have a significant effect on their bottom line. Did you know, when the INR-USD exchange rate moved from 60 to 70 in December 2015, it had an impact of around 20% on Digital Innovation?

As the rupee is inching closer to 82 per dollar, the strong dollar has directly impacted the costs of cloud services for Indian businesses. The high cost of storage and computing power, along with bandwidth charges from overseas vendors, has led to a huge increase in the effective rate of these services. This is especially true for startups and SMEs that rely on cloud computing to store and process user data. With the strong dollar continuing to impact the cost of cloud services, it is essential for Indian companies to evaluate their options and adopt local alternatives wherever possible. This blog post will discuss how the strong dollar impacts cloud costs, as well as potential Indian alternatives you can explore in response to this global economic trend. 

What is a Strong Dollar?

A strong US dollar($) is a term used to describe a situation where a US’s currency has appreciated in value compared to other major currencies. This can be due to a variety of factors, including interest rate changes, a country’s current account deficit, and investor sentiment. When a currency appreciates, it means that it is worth more. A strong dollar makes imports more expensive, while making exports cheaper. Strong dollars have been a growing trend in the past couple of years. As the US Federal Reserve continues to hike interest rates, the dollar strengthens further. The rising value of the dollar means that the cost of cloud services, especially from hyperscalers based in the US, will rise as well. 

Increase in Cloud Costs Due to Strong Dollar

Cloud services are essential for modern businesses, as they provide easy access to software, storage, and computing resources. Cloud services are delivered over the internet and are typically charged on a per-use basis. This makes them incredibly convenient for businesses, as they can pay for only the resources they actually use. Cloud computing allows businesses to scale their resources up or down, depending on their current business needs. This makes it suitable for startups, where demand is uncertain, or large enterprises with global operations. Cloud computing is also inherently scalable and allows businesses to quickly react to changing business needs. Cloud computing is a very competitive industry and providers offer attractive prices to attract customers. However, these prices have been impacted by the strong dollar. The dollar has strengthened by 15-20% against the Indian rupee in the last few years. As a result, the costs of services such as storage and bandwidth have increased for Indian companies. Vendors charge their Indian customers in Indian rupees, taking into account the exchange rate. This has resulted in a significant rise in the costs of these services for Indian companies.

Why are Cloud Services Becoming More Expensive?

Cloud services are priced in US dollars. When the dollar is strong, the effective price of services will be higher in Indian rupees, as the cost is not re-adjusted. There are a couple of reasons for this price discrepancy. First, Indian customers will have to pay the same prices as American customers, despite a weaker Indian rupee. Second, vendors have to ensure that they make a profit.

Possible Indian Alternatives to Cloud Services

If you're looking for a cost-effective substitute for services provided by the U.S.-based suppliers, consider E2E Cloud, an Indian cloud service provider. When it comes to cloud services, E2E Cloud provides everything that startups and SMEs could possibly need.

The table below lists some of these services and compares their cost against their US equivalents. 

According to the data in the table above, Indian E2E Cloud Services are much cheaper than their American equivalents. The difference in price between some of these options is substantial. When compared to the prices charged by suppliers in the United States, E2E Cloud's bandwidth costs are surprisingly low. Although not all E2E Cloud services will be noticeably less expensive. Using Indian services, however, has an additional, crucial perk: data sovereignty.


The price of cloud services will rise as the US Dollar appreciates. Indian businesses will need to find ways to counteract the strong dollar's impact on their bottom lines. To do this, one must use E2E Cloud. The availability of E2E Cloud services in INR currency is a bonus on top of the already substantial cost savings. An effective protection against the negative effects of a strong dollar.

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Actions CEOs can take to get the value in Cloud Computing

It is not a new thing to say that a major transition is on the way. The transition in which businesses will rely heavily on cloud infrastructure rather than having their own physical IT structure. All of this is due to the cost savings and increased productivity that cloud technology brings to these businesses. Each technological advancement comes with a certain level of risk. Which must be handled carefully in order to ensure the long-term viability of the technology and the benefits it provides.

And CEOs are the primary motivators and decision-makers in any major shift or technological migration in the organization. In the twenty-first century, which is a data-driven century, it is up to the company's leader to decide what and how his/her organization will perform, overcome the risk and succeed in the coming days.

In this blog, we are going to address a few of the actions that CEOs can take to get value in cloud Computing.

  1. A Coordinated Effort

As the saying goes, the more you avoid the risk, the closer it gets. So, if CEOs and their management teams have yet to take an active part or give the necessary attention that their migration journey to the cloud requires, now is the best time to start top-team support for the cloud enablement required to expedite digital strategy, digitalization of the organization, 

The CEO's position is critical because no one else can mediate between the many stakeholders involved, including the CIO, CTO, CFO, chief human-resources officer (CHRO), chief information security officer (CISO), and business-unit leaders.

The move to cloud computing is a collective-action challenge, requiring a coordinated effort throughout an organization's leadership staff. In other words, it's a question of orchestration, and only CEOs can wield the baton. To accelerate the transition to the cloud, CEOs should ask their CIO and CTO what assistance they require to guide the business on the path.

     2. Enhancing business interactions 

To achieve the speed and agility that cloud platforms offer, regular engagement is required between IT managers and their counterparts in business units and functions, particularly those who control products and competence areas. CEOs must encourage company executives to choose qualified decision-makers to serve as product owners for each business capability.

  1. Be Agile

If your organization wants to benefit from the cloud, your IT department, if it isn't already, must become more agile. This entails more than simply transitioning development teams to agile product models. Agile IT also entails bringing agility to your IT infrastructure and operations by transitioning infrastructure and security teams from reactive, "ticket-driven" operations to proactive models in which scrum teams create application programme interfaces (APIs) that service businesses and developers can consume.

  1. Recruiting new employees 

CIOs and CTOs are currently in the lead due to their outstanding efforts in the aftermath of the epidemic. The CEOs must ensure that these executives maintain their momentum while they conduct the cloud transformation. 

Also, Cloud technology necessitates the hire of a highly skilled team of engineers, who are few in number but extremely expensive. As a result, it is envisaged that the CHRO's normal hiring procedures will need to be adjusted in order to attract the proper expertise. Company CEOs may facilitate this by appropriate involvement since this will be critical in deciding the success of the cloud transition.

  1. Model of Business Sustainability 

Funding is a critical component of shifting to the cloud. You will be creating various changes in your sector, from changing the way you now do business to utilizing new infrastructure. As a result, you'll have to spend on infrastructure, tools, and technologies. As CEO, you must develop a business strategy that ensures that every investment provides a satisfactory return on investment for your company. Then, evaluate your investments in order to optimise business development and value.

  1. Taking risks into consideration 

Risk is inherent in all aspects of corporate technology. Companies must be aware of the risks associated with cloud adoption in order to reduce security, resilience, and compliance problems. This includes, among other things, engaging in comprehensive talks about the appropriate procedures for matching risk appetite with technological environment decisions. Getting the business to take the correct risk tone will necessitate special attention from the CEO.

It's easy to allow concerns about security, resilience, and compliance to stall a cloud operation. Instead of allowing risks to derail progress, CEOs should insist on a realistic risk appetite that represents the company plan, while situating cloud computing risks within the context of current on-premises computing risks and demanding choices for risk mitigation in the cloud.


In conclusion, the benefits of cloud computing may be obtained through a high-level approach. A smooth collaboration between the CEO, CIO, and CTO may transform a digital transformation journey into a profitable avenue for the company.

CEOs must consider long-term cloud computing strategy and ensure that the organization is provided with the funding and resources for cloud adoption. The right communication is critical in cloud migration: employees should get these communications from C-suite executives in order to build confidence and guarantee adherence to governance requirements. Simply installing the cloud will not provide value for a company. Higher-level executives (particularly the CEO) must take the lead in the digital transformation path.

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