The world of analytics is growing by the day. Organizations, irrespective of size, are using different platforms to tackle day-to-day tasks.
To make well-informed, data-driven solutions, such enterprises often need to employ analytical platforms to do their bidding. So, what is a data analytics platform, and how can you choose one that works best for your organization?
What is a data analytics platform, and why do organizations need one?
Analytics platforms, often regarded as business intelligence (BI) platforms, provide an essential tool for organizations to absorb, organize, and analyze data. Businesses use these to derive actionable insights to improve day-to-day decision-making and enhance business strategy.
Some of these platforms require IT teams to build the analytical environment, connect to various sources, and prepare the data for use. On the contrary, many other platforms function in a plug-and-play format, which might require little or no intervention from IT teams.
Data analysts, business analysts, data scientists, and other business stakeholders can utilize such platforms to prepare, model, and transform their data to make effective decisions in the short and long run.
End-to-end analytics solutions should ideally incorporate five elements:
- Data preparation
- Data modeling
- Data blending
- Data visualization
- Insights delivery
Analytics platforms need to support data blending and data modeling so that the end-user can combine data across different databases. Reports, dashboards, visualizations, and other data-centric modules are created using this data and broken into granular-level data. Granular level data depicts connections and establishes trends between varied datasets, which are converted into visualizations and elaborate reports.
How to Choose a Data Analytics Platform
Despite the number of tools on the market, choosing the right data analytics platform isn’t so daunting once you have the right set criterion.
1. Business Objectives
Business objectives play an integral role in deciding the right platform for your data and business needs. Identify your core objectives, and then break them down into measurable goals. Finally, fit these into an analytical platform, which includes these requirements and gives you the best possible way to achieve your goals.
2. Data Sources
Another critical factor is the platform’s connectivity to different data sources. It’s the time of the cloud, enterprise data warehouses, big data processing, data lakes, specialized NoSQL, and columnar databases. A platform should connect to different data sources seamlessly so that data deliveries are not a thing of the past, but a thing to usher in the future.
With so many pay-as-you-use models, pricing plays a vital role in this crucial decision. Why pay more when you can pay for only the amount of data transmitted from one endpoint to another? Additionally, such platforms offer different pricing models to organizations, depending on the usage, the type of features provided, and the additional costs of data security, maintenance, etc.
4. Data Security
Probably, security is one of the most pertinent factors an organization can’t afford to overlook. Given the high-level security breaches, there is a continued focus on maintaining data security and ensuring a secure, robust way to secure customer and other organizational data. Data platforms usually provide inbuilt security features, spearheaded towards protecting and safeguarding all forms of data against different cyber threats.
Top 9 Data Analytics Platforms
Kloudio is tailor-made for non-technical people who don’t know SQL and other database query languages. It allows you to connect to various data warehouses, data lakes, and data sources using Google Docs and Google Sheets. Additionally, it is also adept at automating, scheduling reports, and running SQL queries within Google Sheets via the Adhoc Query feature, to fetch data automatically.
Gone are the days when you needed to have an eternal dependency on the IT team to do all the dirty work for you. Organizations like Kloudio make life easier by designing platforms that connect seamlessly to a series of data sources and pull information into one single Google Sheet/Google Doc. These data files can create automated reports, which are repeatedly scheduled and refreshed at predefined intervals.
Create elaborate graphs, design visualizations with the gathered data, or simply schedule and automate your existing reports. There’s power in the hands of users, especially those who don’t want to get into the nitty-gritty of elaborate SQL queries.
Tableau Desktop enhances the value of data-driven decisions through the power of visualizations. The visualization software is well-equipped to connect directly with hundreds of data sources (on-premises or in the cloud) and makes it relatively easy for users to perform detailed analysis.
Use Tableau’s interactive dashboard functionality and its intuitive drag and drop features to discover actionable insights, all from its visual interface. Build and embed powerful calculations, create trend lines, and foresee statistical summaries, to better understand your data. Tableau supports your organization’s entire analytics journey, from start to finish, as it takes you from data preparation and deep analysis to driving and sharing insights effectively.
Qlik Sense is a modern-day platform, which sustains self-service analytics and data literacy for an organization’s users. Its capabilities include assisting users with self-service visualizations, data explorations, guided analytics, custom and embedded analytics, and mobile analytics and reporting. It does all this within a governed, multi-cloud architecture that delivers trust and helps scale requirements, as per the need of the hour.
Additionally, Qlik Sense features an unmatched associative exploration and search functionality; this further assists in innovative visualizations, geographic and advanced analytics, self-service creation and data preparation, storytelling and reporting, full collaboration, and a new Insight Advisor.
Power BI puts the world of visual analytics at your fingertips. With this innovative authoring tool by your side, you can create interactive data visualizations and reports in a matter of minutes.
Use your data as you please; connect, model, transform and visualize your data for better use. Place visuals where you desire; analyze, explore and share your data effortlessly by publishing it on the Power BI web service.
Since Power BI Desktop is a by-product of the Power BI product suite, you can easily monitor critical data, share dashboards, and even use the Power BI web for simplifying ongoing tasks.
Sisense is yet another data analytics platform offering data transformation and simplicity features to the end-users. Mashup data across varied data landscapes or transform it for further use into actionable analytics applications; the choice is yours.
Organizations like GE, Wix, Nasdaq, Philips, and many others use Sisense to accelerate their growth, lead to innovation, and drive digital transformation into their businesses.
If you are looking for an all-rounder platform, then ThoughtSpot is every organization’s dream come true. Query datasets using natural language within ThoughtSpot, as it offers a pick-up-and-play approach to its native analytics. Use their UI features; these create autonomously curated feeds that help provide real-time insights into what’s going on behind the scenes with your data.
SpotIQ, ThoughtSpot’s AI-powered assistant, uses machine learning to adapt and understand user’s thoughts and then further provides suggestions related to missed insights. An ideal solution for people who want everything done in a few limited clicks.
Let’s face it; Apache Spark is a mature open-source platform that has become incredibly popular ever since its inception six years ago. It consists of a rich ecosystem of plugins and extensions which are needed for any enterprise data analytics platform, especially the inbuilt MLib machine learning library.
Apache Spark also boasts of a vast user community, which offers its support when needed. The application integrates with other Apache projects like Hadoop, making it a good platform to use when dealing with Big Data.
SAS is undoubtedly one of the earliest players in the analytics market, and it has retained its position over the years with its suite of products and offerings. SAS has built on its visualization capabilities with the Visual Analytics component, which is enhanced manifold post its launch. It allows users to keep their entire workflow on one platform, making the user’s lives much more accessible and organized.
The MicroStrategy platform is known for its complete set of business intelligence and analytics capabilities. These enhancements aim to enable organizations of varying sizes and maturity to derive value from their inherent data.
Organizations often use MicroStrategy’s services to build and deploy analytical and data discovery applications. These applications can further create reports, dashboards, pixel-perfect documents, mobile applications, and much more.
MicroStrategy offers organizations the use of its tool, HyperIntelligence, which boasts of being the first tool to bring insights to employees with no clicks whatsoever.
Time to Choose Your Data Analytics Platform
A data analytics platform is necessary for every organization looking to enhance their reporting capabilities with a view to make meaningful decisions from their collected data. As data is collected and stored in huge repositories, there is a need to have a platform that can wrangle, transform, manipulate and visualize the available information so that it just does not remain a set of vague facts and figures.
Kloudio, on the other hand, offers a free account, letting the end-users try out their inbuilt products and services for a limited period. If you are rearing to give it a whirl, go ahead and build your free account today. Create your free Kloudio account