The world is becoming increasingly data driven. Our everyday reality now is a hugely interconnected world society with data points on everything from what we want to purchase to how many times we braked too hard on our last road-trip. Without data, businesses cannot succeed and expand. They may have a stream of data coming from different sources, but it is useless without analytics. But did you know the next big thing in data analytics and reporting is your IDE software?
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Why should we care about data?
Data is a critical asset for businesses as it helps them make informed business decisions. Plus, data usage drives the success of a business. Which depends on analytics, and the usage of reporting tools. Reporting tools make all the information easier to parse. Without analytics and reporting tools, informed business decisions are hard to imagine. This is where Yellowfin comes into play.
Gartner surveyed CIOs for analytics and reporting tools. They asked for their best pick in business’s success. As a response, the highest 24% voted for data analytics. CIOs also believe that data analysis is important to act on data. Which returns invaluable insights.
So, if an enterprise wants to succeed, it must keep up with the latest trends in data analytics. Don’t know where to look? No worries! We have prepared this guide solely for this purpose. Continue reading to learn about big things in data analytics and reporting tools.
What are the big things in analytics and reporting tools?
What are contextual analytics?
Contextual analytics is a chart embedded on the page with the data. It also includes picturing and the related actions for better insights.
It embeds dashboards and analytics solutions into a software application’s core workflows. In addition, users get the benefits of analytics directly in the framework.
Before contextual analytics, the users had to switch away from their working environments. They did so to investigate data or derive insight. But now, with contextual analytics, the data is delivered to the end-user directly. It is in the user interface and the transaction flow. With one click, users can get instant, guided, and dynamic insights. Which helps them to train and make decisions while working as usual.
The contextual analytic’s goal is to maximize the business benefits. It does so by supporting or triggering actions users take within the app.
What are augmented analytics?
Augmented analytics uses enabling technologies like AI and machine learning. It helps with data preparation, insight explanation, and insight generation.
Its primary purpose is to boost how users explore and analyze data in analytics and BI platforms. It augments the expert and citizen data scientists. It speeds up machine learning, data science, and AI model development.
So, augmented analytics is transforming how businesses prepare data. It helps find insights and share the findings from those insights. It will be no surprise if data analytics becomes mainstream. It is one of the next big things in analytics and reporting tools. Thus, data and analytics leaders should not wait and incorporate it now.
What are automated analytics?
Automated analytics detect relevant anomalies, trends, and patterns. Once found, it delivers insights to users in real-time with no manual analysis.
Enabling technologies like machine learning and AI are used to monitor working performance. They also help search large datasets and track user-defined metrics with desired business outcomes. As a result, it produces alerts of specified triggers and delivers analyzed findings.
The main goal of automated analytics is to perform automated analysis. It offers benefits for both software vendors and end-users. It comes with features of fraud detecting and tracking changes in customer behavior. That helps in automated analytics.
Thus, automated analytics is surely the next important thing to follow.
How do AI Analytics work?
AI tests every possible data combination. It does so to determine hierarchies of relations between data points. One of the main advantages of AI is that it does all this so much faster than any human could do.
In short, artificial intelligence automates the steps that humans would take to complete analysis.
It is worth mentioning that machine learning algorithms are used in AI analytics. They parse through the vast amount of data that enterprise companies gather. With AI analytics, enterprises also identify vital relations that drive business.
How to use Natural Language Query capabilities for analytics and reporting
Natural language query (NLQ) is an ability in BI software solutions. It allows everyday languages to find information users need to make business decisions. It enables users to ask questions about data within their analytics platform.
The analytics users can query data using typed or spoken terms in a search box. The BI systems then compute keywords and search-related databases. It then generates an answer using a report or chart that answers the query. In an ideal case, it helps provide the required insight.
NLQ gives new ways to communicate information between humans and systems. It also explains data and analysis in a way that is accessible to everyone. In addition, NLQ is coming up with a new approach that guides users toward the right questions of data.
Thus, with a guided query experience, NLQ can be vital with analytics and reporting tools.
Develop with IDE software from Embarcadero, track with Yellowfin!
Are you trying to build a business-focused application in a demanding vertical? If yes, Embarcadero’s IDE software is for you. Want to write steadfast code quickly? Embarcadero’s RAD Studio Delphi is for you. Looking for tools to build native apps that are highly developer-focused, multi-platform, and highly mature? You guessed it right, Embarcadero is for you.
But, what if an enterprise or developer wants to integrate data analytics into their platforms? What if they want to monitor and track their application or software’s data? For this, they have Yellowfin.
Yellowfin’s all-in-one package of embedded analytics and reporting tools is great for developers. It allows integration into your Delphi native Windows apps as a fully white-label solution.
It does so with the APIs and REST that aligns with Embarcadero’s RAD Studio, Delphi, and RAD server. Thus, Embarcadero and Yellowfin couple perfectly to cater to the developing and analytics needs.
How does Yellowfin help you do more with data?
Is your traditional analytics tool limited in its capacity and working? Or your existing analytics is outdated and hard to use? Do you want to build a new one? If yes, then Yellowfin has got you covered.
Why Yellowfin? Because, unlike other in-house traditional analytics, Yellowfin’s cost to change is minimal. It is not only modernized but also provides simplicity to its users. Yellowfin also comes with ongoing project support to help enterprises at every step. With competitive pricing and licensing fee, Yellowfin’s acceptance continues unabated.
One of the main advantages of Yellowfin is its white-labeling. Plus, it comes with easy integration with any software or app.
Contact the Yellowfin team today and let Yellowfin analytics help your enterprise grow faster than ever before.