bipp Analytics Unveils Predictions for the Business Intelligence and Data Analytics Industry
BIPP Inc. a modern business intelligence platform that lets companies explore billions of records in real-time, announced its 2022 Business Intelligence and Data Analytics Predictions.
Following two years of disruption and uncertainty, bipp explores the technical and cultural shifts that will shape the business intelligence and analytics industry in 2022 and beyond.
“bipp’s predictions underpin the criticality of the modern data stack,” said Angshuman Guha, CEO, bipp Analytics. “Business intelligence and data analytics platforms are now accelerating cultural, technological, and operational changes within business,” he added.
According to bipp CTO Vishal Joshi, self-service BI, driven by embedded analytics, will be the true 2022 game changer. “With augmented analytics and powerful visual data models and visual SQL, more people than ever before will use BI tools to improve their decision-making.”
Additional highlights from bipp’s 2022 Business Intelligence and Data Analytics Predictions include:
The Data-Driven Company is Dead – Long Live the Culture of Analytics. In 2022, there will be a realization that access to self-service BI alone doesn’t create a data-driven company. Selecting tools that busy business users can easily navigate is a good start. But, beyond a slick interface is a need for robust data models that act as enterprise-wide single sources of truth. If you’re not investing time to define a layer that hosts business logic to be explored by the rest of your organization, then self-service BI will do nothing except create an endless series of helpdesk tickets.
Give people access to tools on their terms by embedding dashboards in the intranets or apps they know. Create trust by ensuring everyone uses the same language to represent critical KPIs and clean data. And combine hands-on training with a platform that can scale your business, recognizing the cultural shift required to take enterprise-wide advantage of BI.
Data Modeling Layers Bring Self-Service (BI) Power to the People. 2022 is the year to get self-service right. IT can be agile enough to support self-service with a data modeling layer by defining reusable data models in one place. SQL expressions and statements represent the layer, which hosts the business logic (so KPIs and metrics are consistent). Modern data modeling layers are built for today’s complex data but should include visual data models, making it easy to create powerful data models without writing code. Instead, teams should interact with the database schema using simple drag-and-drop columns and make edits in real-time.
With this in place, self-service business users can make decisions based on the same trusted logic as the same language represents critical KPIs. So, for example, they can create dashboards, trust their visualizations and easily filter them in real-time. Which means they’re making decisions based on the latest, real-time information.
The Eyes Have IT. In 2022, we’ll embrace the vision-first world of BI. Specifically, data engineers reluctant to learn new languages to create data models will need visual data models. They’ll generate data models with a powerful point-and-click visual interface. And can interact with the database schema using simple drag and drop columns.Analysts can make edits in real-tim e and test the model before committing with a data preview pane. They have access to all of the features of language-created models without writing any code.
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Another related trend will be visual SQL, letting teams blend data and create charts from disparate sources without going through an ETL pipeline. Using an intuitive, flexible drag-and-drop interface, users across a business will explore and visualize data on their terms. They can visually connect to leading databases, and quickly extract and manage data, build charts, and dashboards, all without programming knowledge.
The Revolution Will be Augmented. Augmented analytics is on the fast track in 2022. First, users – and those they report to – need to understand how an insight was generated, whether there’s potential bias or any risks with the underlying data. The augmented analysis takes critical business metrics and lets the platform explore millions of combinations, determine the highest impact, reveal these as facts, and prioritize them in order of importance. All without needing to understand a query language, such as SQL. And with natural language generation, platforms will be able to respond to queries in English and provide context on visuals so users can generate – and justify – insights faster.
The keys here are speed and accuracy. This type of augmented analysis is designed for processing data at scale. And underpinned by trusted data models and being in-database (so processing is conducted within the database), we feel it will help migrate companies from analytics anxiety to analytics culture.
The Year of the Data Engineer. Data engineers will become 2022’s most critical business and technical partners, charged with removing the schism between IT/engineering and other disciplines.
Every business must enable teams with the best tooling while maintaining a unified, flexible data layer. Engineers will need to architect and operate data stacks that solve these problems and be responsible for machine learning, analytic reporting, and decision management.
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