Topic

Big Data Analytics

Big data analytics and information management help organizations enhance the value of information, through smarter storage, integration, virtualization, governance, preparation, and decision-making.

The Origins of Big Data Analytics

Big data analytics helps organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits and happier customers.

Until the era of big data, gaining a 360-degree view of your business through data analysis was a challenge. The solution would generally involve significant spending on powerful data warehouses and relational database management systems, which led to painstaking data preparation in order to answer predetermined questions.

Now, with a massive increase in data volumes and sources, new storage mechanisms and analytical options have emerged, including Hadoop and Blockchain.

The Importance of Big Data Analytics

More and more companies, both large and small, are using big data and related analysis approaches to gain more information, so they can better support their organizations and customers, and benefit fully from the advantages of big data.

Benefits include:

  • Cost Reduction: Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data. Plus, they can identify more efficient ways of doing business
  • Faster, better decision-making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned
  • New products and services. With the ability to gauge market conditions and customer needs through analytics comes the power to give customers what they want. Now, via big data analytics, more companies are creating new products to meet customers’ needs
  • Control online reputation: Big data analytics tools can perform sentiment analysis against very high volumes of online data. Therefore, you can get feedback about who is saying what about your company. If you want to monitor and improve the online presence of your business, big data can help

Big Data Integration and Integrity

Big Data Integration

Big data integration takes traditional data, machine-generated data, social media, web data, and data from the Internet of Things (IoT), and combines it to provide the most complete and up-to-date view of your business. Data must not only be gathered, but its accuracy and usefulness must be ensured. A powerful and broad-reaching data integration framework can help.

Big Data Integrity

According to analysts, 40 percent of all business initiatives fail to achieve their targeted benefits due to poor data quality. Generally, there aren’t many data quality problems with machine-generated data, but there certainly are with other data sources, including big data – and heavy-duty integration needs as well.

Information Builders offers products to manage these initiatives, helping companies leverage powerful data integration and cleansing technologies to ensure data accessibility, consistency, accuracy, and timeliness.

Critical Practice: Big Data Contextualization

Only recently has consistent ROI been delivered by big data initiatives, thanks significantly to contextualization. Big data can be challenging to decipher or interpret in meaningful ways, without ingesting, cleansing, and integrating it with other data assets that provide bigger-picture context. For example, we have customers increasingly leveraging our iWay Software tools to enable big data sources to be contextualized into integrated data sets that support downstream business analysis and processes.

The use of these integration tools maximizes value from big data sources, such as IoT, where machine-generated data is of little standalone value. They eliminate the challenges of fragmented, inaccurate, or incomplete data, and ensure that the resulting information is comprehensive, and of the highest quality at all times. With the big data analytics market estimated to be $203 billion in 2020, ROI is a key driver, and contextualization is key to empowering users to leverage big data in meaningful and relevant ways.

Big Data Analytics With WebFOCUS

WebFOCUS is a fully featured, enterprise-grade BI and analytics platform, capable of delivering a wide range of analytics options to a broad range of users inside and outside the organization. Once your data sources have been integrated, cleansed, contextualized, and governed, let the power of a strategic analytics platform loose on the data. 

Whether a data scientist, data analyst, executive, or operational worker, big data is available for exploration via self-service tools, dashboards, custom apps, or analytical documents. 

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Data Integration

Big Data BI and Analytics

Data Quality

Big Data, Cloud, and IoT Integration