Modern Data Analytics: A Guide For 2023
by Ramesh Panuganty, Founder & CEO
Modern Data Analytics: A Guide For 2023
by Ramesh Panuganty, Founder & CEO
Across organizations, the conversations on Data Analytics are shifting from “What is it?” to “How can we implement it?” as the importance of data-driven decision-making increases. However, organizations still face challenges when it comes to implementing a data-driven culture and recovering value from analytics. As per MIT's 2022 Survey, 62% of Chief Data Officers (CDOs) face difficulty in changing organizational behaviors or attitudes, 55% feel an absence of a data-driven culture or data-driven decision-making, 52% have insufficient resources to accomplish goals, and 47% are concerned about lack of data literacy or understanding in their organization.
With newer technologies emerging to harness data, organizations must review their data analytics strategy for upgrading from traditional analytics systems to modern data analytics platforms.
What is Modern Data Analytics?
Modern data analytics has become an important enabler for digital transformation and data democratization across organizations. A modern data analytics platform comprises of capabilities to extract, store, process, analyze, and present data. These cloud-based SaaS solutions are easy to set up and offer the benefits of scalability, flexibility, and agility.
Organizations have always struggled to extract real value from their data using traditional analytics systems. These systems are rigid, complex to understand, and difficult to scale. With their complex setup and support for limited use cases, their use is restricted to only a small percentage of tech-savvy analysts.
Modern data analytics operates on the core principle of self-service. Business users can execute analytical tasks without requiring help from IT. They can explore data themselves, ask questions in natural language, and get real-time insights for their daily information needs. Modern data analytics makes data accessible, actionable, and consumable for every decision-maker across organizations.
Importance of Modern Data Analytics in Today's Business
Modern data analytics not just offer technological advantages but also contribute to improving management processes and culture across the organization.
From a technology perspective, organizations can democratize data and make their users self-reliant in accessing data and retrieving insights. The advantages of quicker deployments, low infrastructure overheads, any-time and anywhere availability, and high scalability help organizations improve operational efficiencies and realize huge cost savings.
From a management perspective, modern data analytics help establish robust data governance practices by enabling granular access to data. Modern data analytics also offers clear visibility of data quality, thus improving transparency and accountability. This results in creating awareness about quality and ensuring that proper quality processes are followed for keeping data clean and error-free. It also helps organizations increase data literacy, promote a data-driven culture, and bring agility to processes.
Key Components of Modern Data Analytics
Modern data analytics combines the best of machine learning (ML), artificial intelligence (AI), and user-centered design to offer easy-to-deploy and use cloud-native platforms.
Modern data analytics comprises the following components:
- Data Pipeline that connects and ingests data from different sources
- Data Warehouse that stores all collected data
- Data Transformation tool that makes data user-friendly and easy to query
- Data Visualization and BI to present extracted insights in an easily understandable way
- Data Governance policies to manage data security and access
Benefits of a Modern Data Analytics Platform
A modern data analytics platform can effectively handle the ever-increasing volume of data, as the world becomes more and more digitized. The following are some benefits of choosing a modern data analytics platform:
- Provides flexibility and cost savings: Since a modern data analytics platform is primarily cloud-based, it saves considerable hardware costs and other maintenance. Also, its plug-and-play deployment ensures faster setups and provides flexibility to scale as business needs change.
- Encourages the culture of self-service and data-driven decisions: As per MIT's 2022 Survey, 70% of CDOs devote 20% or more of their attention to data-driven culture initiatives. A modern data analytics platform can greatly help them in such initiatives. It is a data infrastructure that can be easily managed and accessed by all the stakeholders in the organization. With a focus on self-service, it acts as an enabler for all types of users, thus reducing dependencies on analysts.
- Enables better understanding through data visualization: Data visualization is an important part of any modern data analytics platform. It enables everyone to see and understand their data better. This helps them to make smarter decisions and make better use of their time.
- Ensures data privacy and security: A modern data analytics platform helps to manage access to sensitive data and implement data governance policies while allowing users across the organization to use data for analytical tasks.
Things to Consider While Choosing a Modern Data Analytics Platform
Since every organization is different, it is important to find the right partners who provide a modern data analytics platform that fits your needs. When you are looking for a modern data analytics platform, you have to ensure that the components are able to scale horizontally and elastically depending on your business requirements.
The following are some points to be considered while selecting a modern data analytics platform.
Ease of Setting Up
As per IDC's AI StrategiesView 2021 Survey, 46% of CDOs face difficulties loading data into analytics platforms. However, setting up a modern data analytics platform is much easier today. Most tools in a modern data analytics platform are SaaS tools with plug-and-play features that make deployments faster, without requiring a lot of technical expertise. With the right tools and services, you can set up a data pipeline in minutes that will collect, process, and analyze your data. Choosing tools that offer prebuilt connectors makes data integration quick and effortless.
Powerful Insights with Fewer Efforts
Data is often scattered and siloed in different systems, making it difficult for decision-makers to get a complete view. With a modern data analytics platform, it becomes easy to break these silos, index data from multiple sources, and offer a single touch point from where users can query their data. A modern data analytics platform leverages the benefits of natural language search, artificial intelligence, and advanced machine learning models. This helps users interact with data quickly and effortlessly to extract insights, without any dependencies or delays.
Robust Data Governance and Security
A modern data analytics platform ensures data privacy and security at every component level, from storing and encrypting data to preventing unauthorized access. Data governance policies ensure that the right user has access to the right data. Modern technologies provide protection from data breaches and attacks and ensure compliance with government and organization security policies. Choosing tools that provide total control over data and enable granular access can help organizations open up access to more users and at the same time protect sensitive data.
Interactive Data Visualizations
Effective data visualization enables decision-makers to identify trends and patterns that might be hidden in text-based data. Data presented in a graphical form helps clarify and highlight patterns and relationships within different entities. Common data visualizations include line, bar, and pie charts, stacked charts, scatter plots, tree maps, and so on. Modern data analytics platforms that offer interactive visualizations help users examine data through different viewpoints and provide controls to drill further and explore.
Clear Data Observability
Data observability refers to monitoring, tracking, and triaging incidents to prevent downtime. Downtime occurs when data is inaccurate, partial, missing, or contains errors. It leads to a waste of time and effort and results in inaccurate decisions. A modern data analytics platform that focuses on data observability is a must-have today, especially when data comes through multiple sources and in varied formats. Choosing tools that evaluate data quality on multiple parameters and identify gaps and inconsistencies can help prevent expensive mistakes.
The Right Time to Upgrade from Traditional to Modern Data Analytics
There has never been a good time than now to switch from traditional to modern data analytics. Here are some reasons to upgrade to a modern data analytics platform:
- Protecting sensitive data: The threat of cyber attacks is real and old systems can be vulnerable to such attacks. The sensitive data stored on your servers need to be protected with the latest technology stack.
- Preventing data breaches: Upgrading ensures that organizations have the latest protection policies in place to prevent data breaches and other security issues.
- Empowering teams: Users should be able to take advantage of new tools that help them increase productivity and make smart decisions.
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