Tag: Data Visualization

Throughout 2024, data analytics continued to play a crucial role in driving data-based decision-making for B2B companies, while investment in advanced data technologies surged. These new tools offer deeper insights, predictive capabilities, and more sophisticated analytics to improve governance. The tools listed below are equipped with powerful features across BI, predictive modeling, natural language processing, and governance, reshaping the landscape of B2B data analytics.

Here are our expert reviews on the top five data analytics tools that defined 2024 and how each one can help businesses leverage data more effectively.

Key Trends Shaping Data Analytics in 2024

Before diving into the tools, let’s look at some major trends in data analytics for 2024. AI and machine learning have moved from innovative add-ons to essential components that support real-time insights and forecasting. Data quality and governance have become even more significant, with more companies prioritizing structured data environments for better compliance and integrity.

Natural language processing (NLP) has unlocked new capabilities in handling structured and unstructured data, such as analyzing customer sentiment and predicting market trends. The tools in our list excel in seamless integration, AI capabilities, and enhanced governance, addressing these trends.

Tool #1: Power BI — Leading in Visualization

Overview:

Microsoft’s Power BI retains its top position in data visualization and reporting due to its strong integration and user-friendly interface. It makes complex data accessible, empowering B2B teams to make informed decisions.

Key Features:

Seamless Integration with Microsoft Suite: Easy data extraction, manipulation, and analysis.

AI-Infused Predictive Analytics: Predictive models based on past data trends for future insights.

Enhanced Governance and Compliance: Features such as role-based access and data governance, essential for regulated industries.

Best Use Cases:

Highly effective for sales and operations teams looking for real-time analytics. B2B companies can use Power BI’s KPI and data modeling features to optimize customer service metrics and sales funnels.

The best data analytics tool depends on a company’s specific needs, such as scalability, integration ease, and advanced analytics like NLP or machine learning. Tools like Power BI and Tableau lead in visualization, while Looker Studio offers a seamless cloud-native experience. SAS shines in compliance-focused environments, and ML tools offer robust predictive capabilities.

As we look to 2025, AI-driven analytics, real-time decision-making, and embedded data tools are set to continue their rapid growth. Each of these five tools laid the groundwork in 2024 and will continue shaping the data analytics landscape in the years ahead.

To Know More, Read Full Article @ https://ai-techpark.com/top-5-data-analytics-tools-2024/

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Business in a dynamic environment no longer considers data a luxury; it’s the fuel that makes wise decisions and drives business success. Imagine real-time insights at your fingertips regarding your customers or the ability to identify operational inefficiencies buried in data sets. Be empowered to drive growth by making data-driven decisions that enable you to optimize marketing campaigns and personalize customer experiences.

However, unlocking this potential is where many of the SMBs struggle. Traditional data analytics solutions often come with fat price tags, thereby positioning themselves beyond companies with limited resources. But fear not! That doesn’t mean it has to be a barrier to entry into the exciting world of data-driven decision-making.

What are data democratization and self-service analytics?

Data democratization means extending access to organizational data to all employees, regardless of their technical nature. It essentially rests on the very foundation that the availability of data should be such that everybody in the entity can get access to information for making decisions and creating a culture that is transparent and collaborative in nature.

Self-service analytics involves tools and platforms that allow users to perform analysis on their own, outside the IT department. They are designed to be user-friendly enough for people in other functions within a company to generate reports, visualize trends, and extract insights on their own from any data they may want.

For small and medium-sized businesses, the benefits that come from data democratization and self-service analytics are huge:

Empower Employees to Make Data-Driven Decisions:

Arm workers at all levels with the ability to make more informed decisions that will have improved outcomes and innovative implications by providing them with relevant data and the proper tools with which to analyze it.

Improve Operational Efficiency:

Much of this IT bottleneck is removed through self-service analytics, improving operational efficiency and increasing decision-making at high speeds.

Gain Insights from Customer Data:

With data democratization, SMBs can get a closer look at customer behavior and preferences to ensure better customer experiences and focused marketing.

Basically, data democratization and self-service analytics democratize the power vested in data to drive efficiency, innovation, and growth within SMBs.

To Know More, Read Full Article @ https://ai-techpark.com/data-democratization-and-self-service-analytics/ 

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In the data-driven world, data visualization is the ultimate BI tool that takes large datasets from numerous sources, aiding data visualization engineers to analyze data and visualize it into actionable insights. In the data analysis process, data visualization is the final chapter that includes a variety of graphs, charts, and histograms in the form of reports and dashboards to make the data more friendly and understandable.

Therefore, to create a data analysis report that stands out, AITechPark has accumulated the top five most popular data visualization tools. These data visualization tools will assist data visualization engineers, further help businesses understand their needs, and provide real-time solutions to streamline the business process.

Tableau

Tableau is one of the most popular data visualization tools used by data scientists and analysts to create customized charts and complex visualizations. The users can connect the data sources, which include databases, spreadsheets, cloud services, and other big data references, allowing them to import and transform data for their analysis. However, Tableau is not the right tool for data creation and preprocessing, as it does not support spreadsheet tools for multi-layered operations. Tableau is expensive when compared to other data visualization tools on the market. The cost of Tableau subscriptions varies; for instance, Tableau Public and Tableau Reader are free, while Tableau Desktop is available for $70/user/month, Tableau Explorer for $42/user/month, and Tableau Viewer for $15/user/month.

LookerML

LookerML is a powerful tool that helps data teams visualize capabilities and data inputs and create a powerful modeling layer that allows them to turn SQL into object-oriented code. To keep the workflow up and running without any challenges, teams can take advantage of Looker Blocks, a robust library of analytics code. However, beginners will still need some apprenticeship to learn the art of data visualization before working with Looker, as it provides complicated tools that might be difficult to understand at first glance. The tool also comes with pre-defined built-in visualizations that have some fixed standards and specifications, giving limited options for customization. The pricing varies from $5,000 per month to $7,000 per month, depending on the size and usage of the tool.

With the growing reliance on data volume available in the market, organizations have started realizing the power of data analytics, which can source real-time data internally and externally as a predictive and prescriptive source. However, to improve data analysis and visualization, engineers are required to select the right tool that aligns with their business goals and needs. Opting for the right tool will help in curating the vast amount of information without human error, eventually aiding in streamlining businesses.

To Know More, Read Full Article @ https://ai-techpark.com/top-five-best-data-visualization-tools-in-2024/ 

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As we have stepped into the digital world, data science is one of the most emerging technologies in the IT industry, as it aids in creating models that are trained on past data and are used to make data-driven decisions for the business.

With time, IT companies can understand the importance of data literacy and security and are eager to hire data professionals who can help them develop strategies for data collection, analysis, and segregation. So learning the appropriate data science skills is equally important for budding and seasoned data scientists to earn a handsome salary and also stay on top of the competition.

In this article, we will explore the top 10 data science certifications that are essential for budding or seasoned data scientists to build a strong foundation in this field.

Data Science Council of America (DASCA) Senior Data Scientist (SDS)

The Data Science Council of America’s (DASCA) Senior Data Scientist (SDS) certification program is designed for data scientists with five or more years of professional experience in data research and analytics. The program focuses on qualified knowledge of databases, spreadsheets, statistical analytics, SPSS/SAS, R, quantitative methods, and the fundamentals of object-oriented programming and RDBMS. This data science program has five trackers that will rank the candidates and track their requirements in terms of their educational and professional degree levels.

IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate is an ideal program for data scientists who started their careers in the data science field. This certification consists of a series of nine courses that will help you acquire skills such as data science, open source tools, data science methodology, Python, databases and SQL, data analysis, data visualization, and machine learning (ML). By the end of the program, the candidates will have numerous assignments and projects to showcase their skills and enhance their resumes.

Open Certified Data Scientist (Open CDS)

The Open Group Professional Certification Program for the Data Scientist Professional (Open CDS) is an experienced certification program for candidates who are looking for an upgrade in their data science skills. The programs have three main levels: level one is to become a Certified Data Scientist; level two is to acquire a Master’s Certified Data Scientist; and the third level is to become a Distinguished Certified. This course will allow data scientists to earn their certificates and stay updated about new data trends.

Earning a certification in data science courses and programs is an excellent way to kickstart your career in data science and stand out from the competition. However, before selecting the correct course, it is best to consider which certification type is appropriate according to your education and job goals.

To Know More, Read Full Article @ https://ai-techpark.com/top-5-data-science-certifications-to-boost-your-skills/ 

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