The Analytics Landscape by Jaspersoft
The analytics landscape has grown to cover a broad area across specialized solutions that cover the presentation layer, middleware and data store along with analytic applications that take on a solution-oriented view.
Within the presentation layer reporting, analysis, advanced analytics and dashboards are considered. Reporting can either be static or ad hoc. On one hand, static reporting means that the lay-out as well as the queries that define the data within the report are static. Ad hoc, on the other hand, allows a business user to create new reports from scratch, on-the-fly. In addition, the reports may be deployed in either an operational reporting or production reporting manner.
Nearly every person in an organization from average business user to analyst to executive could make use of both static and ad hoc reporting. Jaspersoft provides several open source and commercial products to manage static reporting including JasperReports (LGPL license) reporting library for developers, iReport (GPL v3 license) - a graphical desktop report designer built on JasperReports and JasperServer Community Edition (AGPL v3) license - a report server that lets you manage reports in a secured repository. iReport delivers very powerful and flexible ad hoc reporting to developers and power users and JasperServer Professional Edition provides all the features of JasperServer Community Edition and extends those to deliver ad hoc reporting for business users.
Whereas reporting is about outputting data to answer a pre-defined question, analysis is about interacting with data and discovering trends in data. In the 1990's 'OLAP' was considered nearly synonymous with 'analysis.' With OLAP, business users can ‘slice-and-dice’ data, that is view data with respect to different dimensions (shared or private) such as sales, geography, and time. In order to achieve OLAP in a relational database (ROLAP), a technical person maps the OLAP schema to an underlying physical data structure such as an OLTP database but more commonly a data warehouse or data mart‘s star schema or snowflake schema. The benefits of ROLAP include the ability to handle large volumes of data and take advantage of the underlying database system’s SQL capabilities as well as the hardware resources for processing queries.
Executive management as well as business analysts working with very large sets of data, typically in data warehouses that are commonly fed by a vast range of data sources that require much data transformation make use of these analysis tools and from the Jaspersoft stable: JasperAnalysis is an extension of JasperServer and provides powerful ROLAP capabilities, on top of a choice of OLTP or analytic database, via a web browser and JasperAnalysis uses an MDX (multi-dimensional expression) query language to manipulate the data for analytic purposes.
The benefits of an in-memory analysis solution are clear: speed, simplicity, and insight. JasperServer offers in-memory analysis techniques that Jaspersoft refers to as "fully-integrated" in to the reporting and dashboard server environment. In this sense, JasperServer's in-memory analysis capabilities share underlying metadata as well as ad hoc reporting and dashboard-building tools that are common within the Server architecture.
Advanced analytics includes the more advanced domains traditionally associated with analytics. Whereas reporting and analysis tools are typically presenting what happened, advanced analytics tools take historical data to try to predict what will happen based upon previous data patterns. The two market share leaders in the advanced analytics segment are SAS and R. SAS is the largest privately held software company in the world and has specialized in statistical analytics since its inception in the 1970‘s. R is the leading open source advanced analytics environment that rivals and soon will surpass, if it has not already, SAS in audience size. Typically technical analysts working with vast data sets are users of advanced analytics. Jaspersoft provides JasperServer which exposes the output of advanced analytic tools, for example from R, as a dashboard component.
Aside from the e-mail client, dashboards are often thought of as the home base for a business user. A dashboard means different things to different business users depending upon their profile. On one hand, a sales executive will typically want a dashboard showing the status of their lead funnel and sales revenues across geography for the current quarter. On the other hand, an average business user might want to mash-up content that includes reports regarding their daily or weekly responsibilities as well as personalized content that could include geographically related information such as this week‘s local weather or travel information intermingled with corporate data.
Where the data is stored, managed, and queried typically becomes a bigger consideration with the increase in: volume of data, numbers of users, and complexity of queries. You may decide to use your existing OLTP operational system(s) for analytics projects but you may need a separate data store from your OLTP/application because of the degradation of OLTP system or multiple data sources required. However, as analytic workloads increase, you may be required to design a specialized and dedicated system to accommodate them.
The Analytic database segment arose due to the realization that analytic workloads have much different requirements, such as primarily querying data, versus those of the traditional systems where the primary focus is transactions. All ranges of business users realize the benefits of the data store used for analytics. This segment is particularly important for power business users who have complex queries for high-volumes of data. The Jaspersoft Business Intelligence Suite offers reporting, analysis, dashboards, and ETL and supports a wide range of OLTP and analytic databases as data sources.
The often overlooked and underestimated category of middleware serves as the crucial backbone to any serious analytics implementation and its relevance increases particularly for mid-sized and enterprise organizations. Extract-Transform-Load (ETL) is typically the bread-and-butter middleware for any analytics implementation. JasperETL, powered by Talend, is an ETL tool that provides a graphical front-end to manage either ETL or E-LT, and the languages used are a choice of Java, Perl, or SQL.
Analytic applications such as Business Performance Management gives organizations a top-down framework, with an iterative feedback loop built-in, by which to align planning and execution, strategy and tactics, and business unit and enterprise objectives. Users of these applications such as executive and management team members responsible for specific business units, and any staff managing budgets can use JasperServer as the front-end to visualize an analytic application solution.
Whatever your analytic needs, the Jaspersoft ecosystem provides the most efficient, robust and scalable solution, even as explosions in data accelerate and the market demands ever increasing insight.