IBM TM1, Agentic AI & Finance Transformation Insights

Writing rules can save a lot of trouble also can be tedious sometime, but what’s more troublesome than writing rules?! feeders ofcourse. One or the other time we all have wandered in the “feeder”land thinking if there was a way out. No matter how efficient we think we write the feeders, there are times it can mysteriously lead to underfeeding or overfeeding. So, this blog explains the scenarios of how feeding a consolidation, feed from a consolidation work and how it contributes to overfeeding. And this can help to take different approach next time you think of feeders and make it not so ...

Quick Answer: Predictive analytics uses statistical models and machine learning to forecast future outcomes, while prescriptive analytics goes further by recommending specific actions to optimise business decisions using IBM Decision Optimisation. Predictive analytics: Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. A way to predict the future using data from the past. Predictive analytics brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive ...

This article talks about Business Intelligence and Business Analytics, things in common and about differences between one another. This blog also talks about the paybacks for an organization once these are adopted. Let’s start ... Though Business Intelligence and Business Analytics sound similar and are being used interchangeably by many, they do have differences. Business Intelligence ( BI ) :- Term Business Intelligence, though exist for long, have been used by wider audience from late 90s . Intelligence with in Business comes from the data being captured. Business Intelligence has been ...

As we have entered to this era of Data, we might be thinking that why is this Data Science field is so popular ?, why are companies and multinationals investing so much on this field of Data Science?. The answer is simple, because they are making profit out of it. This field has become very crucial and popular in todays market. Now let’s see the definition of Data science, according to Wikipedia Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Some of the common ...

There’s no question that more and more enterprises are employing analytics tools to help in their strategic business intelligence decisions. But there’s a problem - not all source data is of a high quality. Poor-quality data likely can’t be validated and labelled, and more importantly, organisations can’t derive any actionable, reliable insights from it. So how can you be confident your source data is not only accurate, but able to inform your business intelligence decisions? It starts with high-quality software. Finding the right software for business intelligence There are numerous business ...

Smart businesses are seeking out new ways to leverage the benefits of their big data analytics programs, and the self-service model is coming up trumps. By placing the onus directly on business users, enterprises are empowering customers with insights-driven dashboards, reports, and more. But it’s not the only bonus. Arguably an even greater upside for organisations is that it alleviates the talent shortage that often comes with big data. With most companies only employing a handful of data experts who can deliver analytics insights to customers, the self-service model means they are freed up ...

Many businesses have already turned to Octane and partnered with us to help turn their data into meaningful insights. So if you've wanted to connect your Planning Analytics to Power BI, you're not alone and now with us you can. Octane has developed a way you can work directly with IBM Planning Analytics (powered by TM1) and Microsoft Power BI! We've had a number of clients who have wanted to integrate Planning Analytics and Power BI without using external proprietary software we at Octane can say that we've answered the market's call. Planning Analytics powered by TM1 is one of the worlds ...

Yesterday I was fortunate to attend an IBM partner day based on IBM Cloud Private for Data or ICPD and thought to write this blog for you who might not know what the platform is or does. This platform balances the individual data needs of your business by providing an integrated self-service, agile, enterprise-ready platform to significantly improve the governance around the collection, organisation, dissemination and analysis of your data but this isn't the best part. ICPD utilises modern microservices applications to enhance your data assets and analysis with machine learning (ML) and ...

What's interesting to note is that Planning Analytics Workspace (PAW) version 2.0.40 and 2.0.41 are combined so that the release of Planning Analytics Workspace 2.0.41 aligns with the IBM Planning Analytics for Microsoft Excel (PAX) release. With several fixes applied to both PAW and PAX in this version; this post will focus more on the enhancements and features. However, should you want to review the fixes, you can find those here. Features: With this release, you will now be able to create and edit drill through rules and processes in Workspace. Also finding users who don't have any ...

The long-awaited release of Planning Analytics 2.0.7 is finally here! I know a lot of you like me were eagerly awaiting this release and in particular wanting to get into the nitty-gritty details of all the documentation and testing. Luckily for those that are not, I have summarised it all into the below — so happy reading there's lots for you and your team to consider. With this release comes some significant enhancements which I'll get to in the section below. We will also part with several items which are marked for depreciation, replaced in some shape or form. As IBM advises: Updates to ...

Forward-thinking enterprises are using business intelligence and analytics to navigate through their digital transformation – one that could see them expand both physically and fiscally at a rapid pace. The ability to harness this data and use it to make business decisions, however, poses challenges. This is particularly true for organisations that haven’t previously had the technology nor the manpower to sift through all the historical data they’ve accumulated in their daily activities. Think about it – by 2020 it’s predicted there will be 5,200GB of data for every individual on the planet. ...

The prevalence of artificial intelligence (AI) can be felt across countless industries, with the technology helping businesses modernise through automation, business analytics, strategy and more. Even governments are recognising how critical AI is to the future of enterprise, with the 2018-19 Australian federal budget committing $29.9 million over four years to bolstering our AI and machine learning (ML) capabilities. So it’s clear that AI is here to stay. But how can you use AI to derive actionable business insights? After all, the point of adopting any technology should be to use it to your ...