Create a Successful Data Strategy to Grow Your Business With Big Data Analytics

When business leaders hear the term “Big Data”, they most naturally think of the massive volumes of data created by omnichannel marketing systems, IoT (Internet of Things) -connected devices, or business applications.

Big Data refers to a large set of structured, unstructured and semi-structured data continuously generated at high speed and volume. Hence, one may say that Big Data typically is a resource with many types of data and the potential for great scale and rapid updates.

The concept of Big Data has been there for a long time. However, today most organizations understand that if they collect all the data that streams into their businesses and analyze it, they get significant value from it, adding value to their business. It is particularly true when you use techniques like artificial intelligence to drive insights from it.

Read our complete blog to learn more about Big Data Analytics and why leading brands will not miss it?

What is Big Data Analytics?

Big Data Analytics is a process of analyzing Big Data and gathering new information to find patterns, correlations, market trends and customer preferences. This uncovered information helps organizations make informed business decisions that, in turn, result in better efficiency, decision making and throughput.

Data analytics technologies and techniques involve applications with elements such as predictive models, statistical algorithms and what-if analysis powered by analytics systems.

How do Big Data Analytics Work?

Big Data analytics is the collection, process, cleaning, and analysis of large datasets that help businesses operationalize their Big Data worldwide. Here is a step-wise description of how Big Data Analytics work:

• Collect Data

  Data collection is different for all businesses. Thanks to today’s technology, companies can garner both unstructured and structured data from several sources. From cloud storage to mobile applications to in-store IoT sensors, complex or diverse raw data are assigned metadata and stored in the Data Lake.

• Process Data

  Once the data is collected and secured, it is organized for getting accurate results on the analytical queries, especially when the data is unstructured or large. Accessible data is growing significantly, which makes processing a tough job for brands. Batch processing is one of the efficient options. It takes the large data blocks over time and is ideal when there is little turnaround time between the analysis and collection of the data.

• Clean Data

  Big and small data required scrubbing to enhance the data quality and offer stronger results. It is essential for the data to be formatted correctly and to get rid of any irrelevant data. Irrelevant data can mislead or provide flawed insights.

• Analyze Data

  It takes time to get all the Big Data into the usable stake. Once it is ready, advanced analytics processes can turn Big Data into valuable insights. Following are the primary data analysis methods:

• Data mining
• Predictive analytics
• Deep learning

For any Big Data and Analytics requirements, connect to us at sales@ksolves.com.

Why will Leading Brands not miss Big Data Analytics?

Businesses can apply Big Data analytics potentially in real time to drive useful insights from it.

Organizations can use Big Data Analytics systems and software to make data-driven decisions that can improve business-related outcomes like more effective marketing, new revenue opportunities, customer personalization and improved operational efficiency. With an effective strategy, these benefits can provide competitive advantages over your competitors.

Businesses use Big Data with advanced analytics to gain value in many ways, such as:

Reducing Cost

Big Data technologies like cloud-based analytics significantly reduce costs while storing large amounts of data, for example, a Data Lake. This storage can be used for Big Data analytics to help organizations find more efficient ways of doing business.

Fast and Better Decision Making

The speed of in-memory analytics combined with the ability to analyze new data sources, such as live streaming data from IoT devices, helps businesses analyze information in real-time and make fast, informed decisions.

For example, Big Data that enables Predictive Analytics (in near real-time) will help your business to keep our global network of demand, production and distribution working well for the most part. Large enterprises as well as modestly sized e-commerce businesses benefit from these insights.

• You can regulate decisions like stock levels and risk reduction, or temporary or seasonal staffing
• Agile supply chain management
• HR (Human Resource) management can become more effective
• Better ability to identify fraud detection, risk management
• Cybersecurity planning guidance that helps you reduce financial losses and avoid potential business threats

Impact of Big Data on Developing and Marketing New Products/ Services

Innovation is not just a matter of inspiration, and Big Data Analytics allows companies an opportunity to find subject areas that are promising for new efforts and experiments. You can now develop data-driven, innovative new products based on the customers’ changing needs and reviews.

If your organization can gauge customer needs through Big Data Analytics, you can offer customers what they want right when they want it. You can predict and deliver the customer’s needs at the right moment.

When a modern business turns to Big Data to understand its customers, It leads to better customer satisfaction and retention.

The wide range of sources to choose from in Big Data are:

• Purchases and support calls
• Financial transactions and credit reports
• Social media activity
• Surveys
• Computer cookies

Ksolves at AI & Big Data Expo 2022

The world’s leading AI & Big Data event series will return to Santa Clara on the 5th-6th October 2022 for all the ambitious enterprise leaders. The Expo showcases cutting-edge technologies like Machine Learning, Decision Science, RPA, Automation Infrastructure, Computer Vision, Voice Technology, NLP, Chatbots and more.

AI & Big Data Expo will bring together key industries for two days to explore the latest technical innovations, trends, implementations and strategies from the world of Artificial Intelligence & Big Data to drive businesses forward.

Key highlights of the event include:

• 5000 attendees
• 250+ speakers from all over the tech world
• 63% Director Level & Above
• 18 Conference Tracks
• 07 Co-located Events

If your business needs intelligent analytics and real time data solutions then AI & Big Data Expo is the opportunity for you. Lets connect at AI & Big Data expo 2022. Ksolves India Limited is one of the leading companies in India that offers technology solutions to all sizes of businesses and its clients from all over the world.

With our 400+ accredited engineers and 24*7 extended tech support, We help businesses and enterprises with AI and Big Data Analytics solutions and consulting that unleash the power to lead business success. We have an experience of more than 10 years of enabling businesses to stay ahead of their competition.

Connect us now at sales@ksolves.com for a free consultation.

Conclusion

With the basic infrastructure in place, your business is almost ready to open the Big Data system to users. Businesses collect data in real-time and analyze Big Data to make immediate, better-informed decisions.

Big Data Analytics will lead you to smarter business moves, more efficient operations, higher profits and happier customers. Working faster and staying agile gives you a competitive edge that your business hadn’t before.