Understanding the Big Data Boom: How to Leverage Analytics and Big Data Platforms

To say that big data is revolutionizing the way we conduct business is the understatement of the century. The digital reporting firm McKinsey Analytics published a report in 2018, called Analytics Comes Of Age, offering all kinds of interesting insights into big data platforms.

According to McKinsey, 50% of business owners report big data and analytics have fundamentally changed the way they conduct sales and marketing.

Big data is still speeding up. Business owners are predicted to be spending $56 billion on big data, annually, by 2020.

Let’s learn how you can make the most of big data platforms and analytics.

How To Make The Most Of Big Data Platforms and Analytics

It goes without saying, but there are numerous big data platforms to choose from. You’ll need to decide which big data platform will best suit your individual needs before you get started.

Examples of Different Big Data Platforms Include:

  • Hadoop clusters
  • Spark
  • NoSQL
  • Traditional databases

Each of these big data platforms has their own format. This means that you’ll need the right analytics engine, depending on you big data’s format.

Redoing your big data platform or your analytics dashboard, however, can be costly and time intensive. You’ll want to decide on all of that ahead of time to make the process as seamless as possible. 

How To Pick The Right Big Data Analytics Solution

There are many, many big data analytics platforms out there. We’ll be focusing on a few of the most popular, to help familiarize you with the landscape.

Hadoop Spark

Hadoop is one of the oldest big data platforms on the market. This means there are a lot of different big data analytics solutions for the software library.

Apache Spark is one of the most popular. Apache is also responsible for Hadoop, so it makes sense that their analytics engine would be one of the most powerful and popular.

Apache Spark features contributions from over 750 different developers from over 200 organizations. Some of the biggest corporations on Earth are already using Spark.

IBM BigInsights

IBM BigInsights is an open-source big data platform that is powerful enough for enterprise-level big data analytics. As an added bonus, it’s also a big data management system in its own right.

IBM BigInsights features a Data Science mode, with deep, powerful visualization tools as well as a development suite.

IBM BigInsights is also available in the cloud, making it even more accessible to enterprises, no matter their size.

KUDU

Real-time analytics is the frontier of big data. Organizations are leveraging the power of accessing, sorting and visualizing large amounts of data

KUDU by Cloudera is an innovative storage system for structured tables. This allows for lightning-fast Hadoop queries, making real-time big data analytics a reality.

KUDU by Cloudera was three years in the making. Its build is solid, dependable, and robust. It was created to contribute to Apache HBase and HDFS.

If you’d like to learn more about big data analytics, check out our 2019 brochure

Want To Learn More About Big Data and Analytics?

Big data is evolving at the speed of thought, as more and more devices get connected to the Internet and produce increasing amounts of data.

Whether you’re looking to master big data platforms or the emerging analytics tools that are hitting the market, you’ll want to sign up for our The Use of Big Data networking lunch.

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