“We are surrounded by data, but starved for insights.”
Jay Baer, Marketing and customer experience expert
As stated by Jay Baer– the data is certainly there, but not everybody uses it. This stands true for the majority of the key world economy players; when it comes to data utilization. Data is what is generated today; when we talk of flourishing businesses. And to make these big enterprises even more profitable, certified data scientists are hired to assist in making these huge numbers talk via key business insights. This data inferring not only helps to understand the constitution of the business realm; but also assists in predicting future business growth patterns.
Ever thought about how you keep getting traffic alerts or social media updates, product recommendations, Google translate running, and much more?
That are clever machine learning applications that are all-pervasive in our everyday life. Data sciences and the realm of machine learning have grown to a stature where practically no sector of the economy is immune from these intelligent advancements being incorporated into practice. With great inventions in place, we as a world community are bound to be a party to this technological revolution. to answer questions such asHow to increase customer footfall or ways to optimize supply chain delivery or how much product is predicted to be sold in the next quarter? – Data science and machine learning platforms are a huge help. USD 57 million is the estimated total value of the business analytics software market in 2023 as per Allied Market Research. As the hybrid deployment is projected to experience the highest growth, Businesswire projects that the big data analytics market is estimated to reach USD 105.08 billion by the year 2027 at a CAGR of 12.3% throughout 2019-27.
These technically-powered tools and platforms can help handle humungous data (structured as well as unstructured), that are usually not supported by any other traditional databases and statistical software. These offer multiple data sources and tools to resolve business problems in real-time. Machine learning engineers support data science professionals to scale and optimize their models conveniently. Numerous data science frameworks are put in place to explore the data, clean and transform it into a meaningful usable format.
Let us understand the 10 top-rated platforms in data science and machine learning that work their magic in bringing life to business enterprises:
- RStudio
RStudio is a popular data science platform that works toward making sense of the huge data and creates free open-source software for data science, scientific research, and technical communication. It offers easy access to technical communications made convenient via its robust open-source software.
- Alteryx
Time is money and today’s corporate world is not interested in investing their time energy and resources into a technology that is time-consuming and leads to lagged decisions. That is the primary reason we have Alteryx, a platform that allows companies to resolve business queries quickly and efficiently. It offers quick access to users to manipulate, analyze, and data output procedures.
- Splunk Enterprise
Splunk has been ranked among the easiest ways to investigate, monitor, analyze and act upon business data. It collects data from any source, including metrics, logs, sensors, stream network traffic, web servers, cloud services, and the like; thereby offering powerful business insights.
- MatLab
MatLab is one of the most efficient programming platforms designed for ML engineers and data scientists to analyze and design systems and products to transform the big data world. MatLablets you take your ideas toanalyze data, develop algorithms,and create models and applications that help run your business smoothly.
- DataRobot
Headed by Dan Wright in 2020, DataRobot helps companies to leverage the insane power of artificial intelligence to help consumers understand data into useful insights.
- IBM SPSS
The IBM SPSS free trial offers a great opportunity for users to access advanced techniques in an easy-to-use package to help find new opportunities to improve efficiency and reduce risks.
- RapidMiner Studio
This visual workflow Data science ML tool makes data scientists more productive from rapid prototyping of ideas to designing mission-centric predictive models. It unifies data preparation, boosting the productivity of employees manifold.
- Jupyter Notebook
Jupyter Notebook is an interactive interface that helps users to configure, create, share and arrange workflows in data science, ML, and scientific computing. A multi-user version of the notebooks helps students, companies, and research labs with centralized deployment features.
- KNIME Analytics
Thinking of visual programming, creating nodes for the entire data science life cycle, tool blending- Think KNIME Analytics. This offers an easy blend of data from any source, clean, sort, filter, aggregate data; and leverage ML and AI benefits manifold.
Backing up your data science skills with the best data science certifications in the world and choosing the best data science frameworks would offer easy access to managed open-source tools and libraries, alongside proving you to be an asset to your organization. With the right combination of skills and expertise, you are sure to scale higher in your data science career in the long run.
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