The landscape of analytics has undergone a dramatic transformation, driven by the increasing complexity of data and the ever-growing demand for timely insights. Legacy BI tools, once the industry standard, are now struggling to keep pace with the evolving needs of modern businesses. The need to modernize these legacy reports has become imperative to unlock the full potential of data-driven decision-making and Generative AI assisted analytics.

Let’s dive into what makes Looker a compelling BI tool and explore modernization challenges when migrating legacy BI from tools like Cognos and Tableau to Looker.

Why Looker for Modern BI

Looker, a powerful data platform offered by Google Cloud, has emerged as a leading choice to modernize BI, especially for companies already using Google BigQuery.

Key Features of Looker for Modern Analytics

Looker offers a unique blend of features that make it an ideal solution for businesses seeking to accelerate time-to-value from their data.

• Intuitive User Interface: Looker’s user-friendly interface empowers business users to explore data independently, reducing reliance on technical teams.
• Semantic Layer: This powerful abstraction layer provides a unified view of data across disparate sources, simplifying data exploration and analysis.
• Advanced Analytics: Looker enables advanced analytics techniques like machine learning and predictive modeling, allowing organizations to uncover deeper insights.
• Customization and Flexibility: Looker can be tailored to meet the specific needs of any organization, with customizable dashboards, reports, and alerts.
• Collaboration and Sharing: Seamless collaboration and sharing of insights across teams foster a data-driven culture.
• AI-Powered Analytics: Gemini in Looker provides AI assisted analytical workflows for more efficient self-service BI.

Why BigQuery Customers Modernize BI Reports in Looker

Specifically for Google BigQuery customers that are using other BI tools, there are many key drivers for modernizing those reports in Looker.

• LookML provides a re-usable data model that is highly efficient within the BigQuery / GCP ecosystem.
• Looker and BigQuery deliver faster query performance – up to 10x improved speeds.
• Looker enables easy integration with BigQuery data sources.
• Looker excels at complex data modeling, customization of reports, and real-time insights into data.
• Looker works well with large volumes of data from multiple sources.

Now that we’ve explored why Looker is worth considering for your modern BI needs, let’s take a look at migration challenges.

BI Migration Challenges

Migrating from legacy BI tools to Looker can be a complex process and can present challenges, including issues related to data migration, report and dashboard reconstruction, user adoption, and integration with existing systems.

Common Challenges When Migrating to Looker

Looker offers unique features that require proven solutions and workarounds to achieve similar or better results when migrating from legacy BI tools.

• Data Model Differences: Each BI platform has different data modelling approaches, leading to discrepancies in data representation and calculations.
• Excel Migration: Looker does not have direct Excel import, so data needs to be extracted and converted.
• User Training Needs: Users familiar with their existing BI tools may have difficulty adapting to Looker’s interface, navigation, and functionalities.
• Data Blending in Looker: Data Blending, a widely used method for combining multiple sources, is not a feature in Looker and requires alternative methods for achieving similar outcomes.
• Visualization Variances: Every BI tool offers its unique set of visualizations or formatting options, impacting the layout and design of dashboards.
• Performance Optimization: Large data sets and complex queries can have an impact on performance without proper query optimization.

Tableau Migration to Looker Success Story

With extensive BI Modernization experience, Bitwise understands the differences between legacy tools and modern tools like Looker. We’ve been through the migration process and have developed solutions to address the unique challenges of migrating to Looker with proven success in keeping BI migrations on track and within budget.

For instance, a leading American ticketing company faced the challenge of maintaining and scaling its existing Tableau reports. As their data volume and complexity grew, they sought a modern, scalable solution to streamline their BI operations and unlock deeper insights. Bitwise solution helped the firm in migrating Tableau Report Migration to Looker while reducing the development and maintenance costs.

Recommendations for BI Modernization

To overcome the challenges mentioned above, a structured approach to legacy BI modernization is essential.

Proven BI Modernization Approach

Bitwise recommends the following approach to ensuring a seamless transition from legacy BI to Looker.

• Assessment: Evaluate the current BI landscape, identify pain points, and define modernization goals.
• Planning: Develop a detailed migration plan, including data migration strategies, report and dashboard mapping, and user training.
• Implementation: Migrate data, build reports and dashboards, and configure Looker to meet specific business needs.
• Testing and Validation: Thoroughly test the migrated environment to ensure data accuracy and report functionality.
• Deployment and User Training: Deploy Looker to end-users and provide comprehensive training to maximize adoption.
• Ongoing Support and Optimization: Continuously monitor and optimize the Looker environment to ensure optimal performance and user satisfaction.

Access our whitepaper on modernizing BI and transforming data into actionable insights to know more about a strategic approach to modernizing your legacy BI environments to become truly data driven.

Achieving BI Modernization Success with Looker

Using the above approach, Bitwise helped a global financial services company that was struggling with a legacy WebFocus-based reporting and visualization application. The company was plagued by high maintenance costs, performance issues, and poor user experience.

To address these challenges, they partnered with Bitwise to modernize legacy reporting on the cloud with Looker. By leveraging Looker’s powerful analytics capabilities, the company significantly improved report performance, reduced costs, and enhanced user experience. The intuitive interface and self-service capabilities empowered users to access real-time data and generate insights more efficiently, driving data-driven decision-making accelerating business growth.

Getting Started

While there are many challenges to modernizing BI in Looker, the benefits can outweigh the challenges and set your organization up for a modern, data-driven future. In addition to using a proven migration approach, Bitwise, a trusted Google Cloud Partner and leading provider of data solutions, offers a range of accelerators and value-adds to expedite the BI modernization process.

Our proven BI modernization methodology will guide you through the entire process, from assessment to deployment. Contact us today to start your BI Modernization journey and accelerate time-to-value with Looker.

The post Accelerating Time-to-Value with Looker: The Future of BI appeared first on Bitwise.

Like many organizations, you may be launching a digital transformation journey that includes migrating major functions to the cloud. It’s critical to modernize your BI environment at the same time in order to take advantage of the benefits of a cloud architecture. An updated BI that provides a single coherent view of business data and self-service reporting helps your organization become truly data-driven.
Bitwise has proven experience helping organizations like yours make the BI modernization journey.

The Challenges of Legacy BI

You may be all too familiar with the major challenges of legacy BI:

• Data siloing—Patchwork legacy BI solutions lead to data siloing rather than providing your business units with access to a “single source of truth.”
• Scalability—On-premises server farms are costly and inflexible. Legacy systems impede your users’ access to new insights, leading to lost opportunities as they wait for IT to service custom report requests.
• Legacy reports and applications—Legacy reports and applications can be hard to use, presenting information in tabular form that users must rearrange manually.
• Performance—With big data, legacy tools exhibit poor rendering and extraction efficiency.
• Security—Legacy tools are often incompatible with newer security requirements.
• Complex data pipelines—To handle diverse data sources, legacy BI systems often require costly, fragile integrations with specialized external tools.

A modern BI solution can solve these problems. Modern BI environments are optimized for cloud storage and swiftly provide a coherent overview of business intelligence. And with self-service, your business users can see exactly the information they need, when they need it, without any need to “massage” generic tabular reports.

An Approach to BI Modernization

Ready to start? Here are some guidelines to help you on your modernization journey, based on the proven Bitwise approach to BI transformation.

Strategy and Assessment

Before modernizing and re-imagining your BI environment, you need to understand it. Document everything you learn. This information will be invaluable as you move through modernization.

Assessment Phase I: Investigation and Discovery

Start by gaining a thorough understanding of your business functions and infrastructure. Look for key features and capabilities in your current environment. Identify who needs what information, how often, and in what form.

Assessment Phase II: Gap Analysis

Look for unmet needs in your BI platform and potential improvements to your analytics, reports, and apps. Think about performance, accuracy, timeliness, and security problems and risks. Consider whether your environment has features that you no longer need. This is a good time to involve your business users.

Assessment Phase III: Conversion Approach and Solutions

Create a strategy to build your new environment, migrate your BI, and fill in the gaps. Build a road map that clearly delineates where you are, where you want to be, and how to get there in a series of realistic steps.
Re-imagine your reports and apps to take advantage of your new environment. Modern BI enables you to move beyond simple static presentations to powerful interactive reports incorporating real-time data visualizations. And self-service empowers your users to create their own rich, interactive reports.
Don’t forget to look for “easy wins” provided by your new environment.
Assess the feasibility of each step. If any aspect of your plan seems unrealistic, now is the time to rethink it.

Architecture choices

The ideal architecture depends on your organization’s needs. You can make choices to prioritize and optimize for scalability, flexibility, manageability, performance, data quality, and a coherent, top-down view of business data. An experienced specialist can help you understand the implications of your choices, so that you can make optimal decisions based on your organization’s goals.

Other design tradeoffs

• Is it more important to roll out your new environment quickly, or to optimize for future extensibility?
• What cloud provider and BI solution are best for you?
• What parts of your design are the top priorities?

Strategy and Assessment Deliverables

When you complete the steps above you should have:

• Project feasibility, describing the effort and complexity
• Gap analysis
• Methodology for creating, migrating, and testing each part of the environment
• Project schedule and implementation roadmap
• Timeline for proof of concept

These deliverables form the basis of your next steps.

Considerations for Selecting Tools

In selecting your cloud platform, BI solution, and other tools, think about factors such as scalability, performance, security, and the specific features you need.

Data Management

Your data architecture can enhance or limit your BI environment’s scalability. The main challenge in your old data architecture is probably the sheer number and complexity of pipelines.

Building modernized pipelines end-to-end

When designing your architecture, aim to integrate data from multiple sources and automate as much as possible. Take advantage of modern data pipelines, which can restructure unstructured data, pre-filter it, and clean it. Your pipelines can deliver data downstream in real time, protected by integrated security and fault tolerance features.

Application Re-engineering

Moving your environment to the cloud is an opportunity to build powerful features into your apps. Start by defining the business process supported by each app. Analyze your workflows for gaps, issues, and omissions. Then identify opportunities for improvement. Don’t just fix issues and satisfy unmet needs—instead, reimagine the app around cloud capabilities and your future goals.
Now select the key opportunities from the previous step as the basis of your app design, map out your new workflows, and, finally, develop, test, and implement the redesigned app.

A Case Study with Looker

A major payment processing enterprise had a goal in mind to help drive growth and expansion: to grow their product portfolio with an enhanced feature set, improved UI and UX, and value-added services. Their customer portal provided access to data analytics, but they wanted to empower users to build better analytics and make better business decisions. The client worked with Bitwise and Google to realize their vision of a cloud based big data strategy and selected Looker as the best fit to modernize its customer portal. Bitwise re-engineered the client’s legacy reports to take advantage of Looker’s advanced capabilities and set up BigQuery data flows for real-time data and self-service access. The result: increased revenue, reduced cost, and rave customer reviews.
Read the case study to learn more about the client’s journey with Looker.

Get Started with the Experts

Your journey to a cloud-based BI environment is an integral part of your digital transformation strategy. Bitwise can help you implement a solid framework to enable future opportunities. Contact Bitwise to schedule a discussion with a Bitwise expert.

The post Modernize Your BI, Accelerate Business Insights appeared first on Bitwise.

Client Challenges and Requirements

• Cut-down on servers
• Reduce maintenance cost
• Better data visualization and data representation
• Make reporting User friendly
• Faster Insights and Ease of Use

Bitwise Solution

• Perform Impact Analysis based on Cost and Resource Utilization to help the business in decision making for reporting tool selection.
• Migrate Cognos Cubes to Tableau Extract / Hyper, Whiteboard and Default views were created to retain the look and feel of Cognos PowerPlay studio and Analysis studio.
• Modify reports with redundant logic to use independently published data sources.
• Develop Charts/Maps and Dashboards for real time tracking of business information.
• Design data sources to be used independently as well as blended when required to reduce redundancies.
• Enhance executive dashboards to provide data alert feature and receive alerts when conditions are met.
• Implement dynamic parameters to optimize query performance and fetch only subset of data.
• Implement data extracts and schedules for periodic data refresh and report distribution. Used intermediate tables for performance optimization.
• Create reports/dashboards for mobile devices for easy accessibility.

Tools & Technologies We Used

Tableau

Teradata

Cognos

Key Results

Excellent visualization and self-service environment

Reduced server and maintenance cost

Real Time Data Tracking Dashboards with important timely alerts

Implementing Story boards and dashboard functionalities

Extract and hyper files feature was leveraged to optimize performance

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The post Report Migration from Cognos to Tableau appeared first on Bitwise.

Client Challenges and Requirements

• Lack of skilled resources within Business
• High Licensing cost

Bitwise Solution

• Export existing Cognos Report to Excel file. Use the file as mockup for Qlik report.
• Setup and Configure required data sources in Qlik.
• Create QVD files to load data from each data base table. Develop data model using Qlik data files (.QVD).
• Establish relationships between different data sources. Historical / point in time data was migrated from Cognos cubes to database.
• Implement Star Schema approach to avoid loop; develop fast and flexible applications.
• Implement role-based data security using section access.
• Schedule the monthly process to push dashboard output to business through email using Nprinting.
• Build dashboards in Qlik and schedule the monthly process to push dashboard output to business through email.

Tools & Technologies We Used

QlikView

QlikSense

Qlik Nprinting

Cognos

Key Results

Excellent visualization with Improved the Scalability, Security and Availability

Reduced server and maintenance cost

Real Time Data Tracking Dashboards

Implementing Story boards and dashboard functionalities

Optimized performance with In-Memory Analysis and Data compressed features

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Bitwise provides comprehensive solution for all your data projects

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The post Report Migration from Cognos to Qlik appeared first on Bitwise.