The growing IAM market trend is clear proof that there is a huge demand for Identity Access Management expertise. IT professionals with ID and access management skills are in high demand because of the increasing growth in the use of cloud computing and mobile technologies.
Businesses utilize and analyze data in almost all operations because it can help them determine the root causes of system failures, attract customers, calculate risk portfolios, detect fraud and much more.
Big data refers to a large volume of either structured or unstructured data. Tools that organize big data collection allow businesses to analyze trends such as customer activity, which helps to guide highly relevant online and offline promotional campaigns. Ultimately, utilizing big data gives a company an edge against competitors that use outdated methods for projection modeling. Beyond significantly reducing costs and boosting operational efficiency, using big data also increases sales and customer loyalty.
With the growing use of big data, careers in this field are also on the rise. Big data skills are in demand across all industries because data is key to unlocking a company’s potential at every stage of the buyer’s journey. Since “big data” is an umbrella term, there are many job opportunities at all seniority levels that offer competitive salaries. Big data job titles include data engineer, data scientist, data analyst, machine learning engineer, business analytics specialist, data visualization developer and more. Professionals in the field use big data tools to help them work more efficiently through reporting and testing.
Top 5 Big Data Solutions
In today’s economy, users move fast. That’s why businesses are increasingly turning to big data tools to improve their daily operations and help them make better-informed decisions. These tools offer a range of big data solutions to uncover hidden patterns, draw correlations and provide insights on technical issues. The most popular big data analysis solutions are available on a subscription basis as software-as-a-service platforms. Listed below are the top five big data tools businesses can use to elevate their analytical insights.
Cloudera is a big data solution that allows users to access many data dimensions in one powerful platform. Data collection is easily scalable and customizable to a company’s needs. Cloudera is also 100% open source, which allows for several integrations. For example, Cloudera can integrate with Amazon Web Services (AWS), Microsoft Azure and Google Cloud.
Cloudera’s features include business intelligence reporting, real-time insights, model scoring and other advanced analytics reporting capabilities. This big data tool provides multiple functions that work together on one platform, eliminating the need for businesses to utilize data silos. Cloudera also has robust security measures to safeguard sensitive information and prevent cybersecurity threats.
2) Apache Hadoop
The Apache Hadoop platform processes large sets of data across multiple devices and servers. Hadoop is scalable, allowing a business to collect and analyze data from thousands of sources.
The suite allows for the storage and processing of data using its MapReduce programming model. It uses data locality, which allows data nodes to process different sets of data at the same time. Businesses can also install other Apache software programs in addition to Hadoop, such as Apache Hive, Apache ZooKeeper, Apache Impala, Apache Flume, Apache Oozie and Apache Storm.
3) Apache Hive
Apache Hive is another popular open-source big data tool. It enables data scientists to analyze multiple sets of data at once and can be used in conjunction with Hadoop. Through Hive, programmers and data scientists can search through large sets of data incredibly fast, using an SQL-like query language.
This big data tool is an excellent investment for businesses because it’s a bit more intuitive compared to the deep complexities and extensive capabilities [LA3] of the MapReduce programming model. Search queries can also be done through a command line, which connects the user to Hive.
4) ETL Tools
ETL (extract, transform, load) tools are a type of software used to pull data from multiple databases. The key benefit of ETL tools is endless customization for a reporting dashboard that provides quick insights. Data can then be uploaded to an organization’s data warehouse or data lake. This type of big data tool is best suited for enterprise organizations that deal with a large and diverse stream of data, as it allows for data integration even over a complex or rapidly changing data architecture.
There are many different ETL tools available for a diverse range of needs, including incumbent batch, cloud-native, open-source and real-time ETL tools. Some of the most popular ETL tools include Informatica PowerCenter, Oracle Data Integrator, Alooma, SnapLogic, Apache Kafka, Talend Open Studio, StreamSets and Confluent.
5) Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics is the most powerful solution to analyze real-time streaming data, gain actionable insights and respond to business and customer needs. This intuitive platform is easy to use and has open-source libraries based on Apache Flink.
Amazon Kinesis Data Analytics allows users to build an application in a matter of hours, since this library includes over 25 operators, which helps to facilitate faster streaming, manipulation and aggregation of data. The platform is also extremely customizable and can program the template to your organization's specific requirements.
Having a deep understanding of big data and how to harness its benefits to make actionable business decisions is essential for companies to maintain a competitive advantage. Empower your team with the skills and knowledge they need to utilize the power of big data in their daily operations. Since 2001, ExitCertified has been a leader in providing in-class and virtual training for the leading IT platforms.