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Business Intelligence Tools Ibm – ARMONK, N.Y. , Nov. 3, 2022 /PRNewswire/ — IBM (NYSE: IBM ) announced new software designed to help enterprises break down data and analytics silos so they can make data-driven decisions quickly and navigate unpredictable disruptions. IBM Business Analytics Enterprise is a set of business intelligence planning, budgeting, reporting, forecasting and dashboard capabilities that provides users with a robust view of data sources across their business. Along with IBM Planning Analytics with Watson and IBM Cognos Analytics with Watson, this suite also includes a new IBM Analytics Content Hub that helps simplify how users discover and access analytics and planning tools from multiple vendors in a single view and dashboard customization.

According to an August 2022 Forrester report, knowledge-driven organizations are 1.6x more likely to report using data, analytics and insights to create experiences, products and services that differentiate them in the marketplace compared to beginners.

Business Intelligence Tools Ibm

. However, companies currently face a highly dynamic operating environment where they must navigate unpredictable events such as supply chain disruptions, labor and skills shortages, evolving regulations, and more. The complexity of storing data in different silos can make this more challenging as teams collaborate across different analytics and business intelligence tools. To become data-driven, businesses can differentiate themselves by creating an enterprise-wide strategy that allows them to bring their tools together and put knowledge in the hands of decision makers.

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Building on IBM’s existing portfolio of business intelligence solutions, IBM Business Analytics Enterprise includes a new IBM Analytics Content Hub. It is designed to enable users to view planning and analytics dashboards from multiple vendors, including tools such as IBM Cognos Analytics with Watson, IBM Planning Analytics with Watson, and other common business intelligence tools in a single view that combines elements of each in a custom-designed dashboard. for their unique needs. Additionally, it features algorithms that can recommend role-based content to help users surface new stories, reports and dashboards from across the organization to aid decision-making. As more users click through materials within the IBM Analytics Content Hub, the solution analyzes usage patterns to recommend content that aligns with their specific interests.

New capabilities for IBM Cognos Analytics with Watson; IBM Planning Analytics with Watson is expected to be available on AWS

With today’s news, IBM Cognos Analytics with Watson, an AI-powered business intelligence solution, now also includes new integration capabilities and improved forecasting that allows users to consider multiple factors and seasons in forecasting -their patterns. In addition, IBM Planning Analytics with Watson, an AI-powered solution that helps simplify financial and operational planning, is expected to be available as a Service on AWS later this year.

IBM Business Analytics Enterprise is designed to help break down silos so the right teams can get the right data at the right time. For example, an organization’s sales, HR and operations teams each need access to data and insights from different business intelligence and planning tools for their specific needs, such as optimizing sales, building workforce forecasts, or forecasting operating capacity. But when it’s necessary to share data and reporting between departments, complexities can arise because those teams are using multiple solutions. This can result in duplicate content across applications, which can threaten data consistency and quality. IBM Business Analytics Enterprise helps make enterprise data more easily shared, while remaining protected and avoiding data duplication by giving users across departments a single point of entry to view the data they require

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“Businesses today are trying to become more data-driven than ever before as they navigate the impending supply chain disruptions, labor and skills shortages and regulatory changes,” said Dinesh Nirmal, General Manager of Data, AI and Automation, IBM. “But to be truly data-driven, organizations need to be able to provide their diverse teams with more comprehensive access to analytical tools and a more complete picture of their business data, without jeopardizing the programs of ‘ their compliance, security or privacy. IBM Business Analytics Enterprise offers a way to bring together analytics tools at a single glance, regardless of which vendor it comes from or where the data resides.”

ALH Gruppe is a leading finance and insurance company in Germany, and with thousands of employees needing access to data insights, the majority of whom are not data scientists or highly technical users, they sought solution to help simplify their data infrastructure even further.

“We have been using IBM Cognos Analytics with Watson for over a decade now to support decision making of all kinds in our business. We often use it in conjunction with other business intelligence tools, and challenge one was that those tools were always standing side by side without any connection between them and the data was separate,” said Bernd Oerthle, Head of Reporting and Infrastructure Analytics, ALH Gruppe. “With the new IBM Analytics Content Hub, we plan to connect internal stakeholders with several different BI solutions for easy access to self-service data, enabling better support for our end customers.”

The launch of Business Analytics Enterprise continues to build on IBM’s strategy to provide businesses with tools to support data-driven decision making. IBM Cloud Pak for Data and IBM business intelligence solutions work together to help customers create a data fabric architecture that simplifies data integration, enabling them to drive their analytics anywhere and take advantage of data in different environments.

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Learn more about IBM Business Analytics Enterprise by reading the blog post or get started today by visiting: https://www.ibm.com/products/business-analytics-enterprise

Statements about IBM’s future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

IBM is a leading global hybrid partner and AI, and business services provider, helping clients in more than 175 countries capitalize on insights from their data, simplify business processes, reduce costs and gain a competitive advantage in their industries. Nearly 3,800 governments and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to impact their digital transformations quickly, efficiently and securely. and business services give open and flexible options to our clients. All of this is underpinned by IBM’s legendary commitment to trust, transparency, accountability, inclusiveness and service. For more information, visit www.ibm.com. Business intelligence (BI) is software that ingests business data and presents it in user-friendly views such as reports, dashboards, charts and graphs. BI tools allow business users to access different types of data — historical and current, third-party and internal, as well as semi-structured data and unstructured data such as social media. Users can analyze this information to gain insight into how the business is performing.

According to CIO magazine: “Although business intelligence does not tell business users what to do or what will happen if they take a certain course, BI is not just about generating reports either . Rather, BI offers a way for people to examine data to understand trends and gain insights.”

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Organizations can use the knowledge gained from business intelligence and data analysis to improve business decisions, identify problems or issues, spot market trends, and find revenue or business opportunities. new.

BI platforms traditionally rely on data warehouses for their basic information. A data warehouse aggregates data from multiple data sources into one central system to support business analysis and reporting. Business intelligence software queries the store and presents the results to the user in the form of reports, charts and maps.

Data warehouses can include an online analytical processing (OLAP) engine to support multidimensional queries. For example: What are the sales for our East region versus our West region this year, compared to last year?

“OLAP provides powerful data discovery technology, which facilitates business intelligence, complex analytical calculations and predictive analytics,” says offering manager Doug Dailey in his data warehousing blog . “One of the main benefits of OLAP is the consistency of information and calculations it uses to move data to improve product quality, customer interactions and process improvement. “

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Some newer business intelligence solutions can extract and ingest raw data directly using technology like Hadoop, but data warehouses are still the data source of choice in many cases.

The term business intelligence was used for the first time in 1865 by the author Richard Millar Devens, when he mentioned a banker who gathered market intelligence before his competitors. In 1958, a computer scientist named Hans Peter Luhn explored the potential of using technology to gather business intelligence. His research helped establish methods for creating some of the early analytics platforms of.

In the 1960s and 1970s, the first data management systems and decision support systems (DSS) were developed to store and organize growing volumes of data.

“Many historians suggest that the modern version of business intelligence evolved from the DSS database,” says the IT education site Dataversity. “During this time a combination of tools was developed, with the aim of accessing and organizing data in simpler ways. OLAP, executive information systems and data warehouses were some of the tools developed to work with DSS.

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By the 1990s, business intelligence grew increasingly popular, but the technology was still complex. It usually required IT support — which often led to backlogs and delayed reports. Even without IT, analysts and users of business intelligence required

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